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Survey Research – Types, Methods, Examples

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Survey Research

Definition:

Survey Research is a quantitative research method that involves collecting standardized data from a sample of individuals or groups through the use of structured questionnaires or interviews. The data collected is then analyzed statistically to identify patterns and relationships between variables, and to draw conclusions about the population being studied.

Survey research can be used to answer a variety of questions, including:

• What are people’s opinions about a certain topic?
• What are people’s experiences with a certain product or service?
• What are people’s beliefs about a certain issue?

Survey Research Methods

Survey Research Methods are as follows:

• Telephone surveys: A survey research method where questions are administered to respondents over the phone, often used in market research or political polling.
• Face-to-face surveys: A survey research method where questions are administered to respondents in person, often used in social or health research.
• Mail surveys: A survey research method where questionnaires are sent to respondents through mail, often used in customer satisfaction or opinion surveys.
• Online surveys: A survey research method where questions are administered to respondents through online platforms, often used in market research or customer feedback.
• Email surveys: A survey research method where questionnaires are sent to respondents through email, often used in customer satisfaction or opinion surveys.
• Mixed-mode surveys: A survey research method that combines two or more survey modes, often used to increase response rates or reach diverse populations.
• Computer-assisted surveys: A survey research method that uses computer technology to administer or collect survey data, often used in large-scale surveys or data collection.
• Interactive voice response surveys: A survey research method where respondents answer questions through a touch-tone telephone system, often used in automated customer satisfaction or opinion surveys.
• Mobile surveys: A survey research method where questions are administered to respondents through mobile devices, often used in market research or customer feedback.
• Group-administered surveys: A survey research method where questions are administered to a group of respondents simultaneously, often used in education or training evaluation.
• Web-intercept surveys: A survey research method where questions are administered to website visitors, often used in website or user experience research.
• In-app surveys: A survey research method where questions are administered to users of a mobile application, often used in mobile app or user experience research.
• Social media surveys: A survey research method where questions are administered to respondents through social media platforms, often used in social media or brand awareness research.
• SMS surveys: A survey research method where questions are administered to respondents through text messaging, often used in customer feedback or opinion surveys.
• IVR surveys: A survey research method where questions are administered to respondents through an interactive voice response system, often used in automated customer feedback or opinion surveys.
• Mixed-method surveys: A survey research method that combines both qualitative and quantitative data collection methods, often used in exploratory or mixed-method research.
• Drop-off surveys: A survey research method where respondents are provided with a survey questionnaire and asked to return it at a later time or through a designated drop-off location.
• Intercept surveys: A survey research method where respondents are approached in public places and asked to participate in a survey, often used in market research or customer feedback.
• Hybrid surveys: A survey research method that combines two or more survey modes, data sources, or research methods, often used in complex or multi-dimensional research questions.

Types of Survey Research

There are several types of survey research that can be used to collect data from a sample of individuals or groups. following are Types of Survey Research:

• Cross-sectional survey: A type of survey research that gathers data from a sample of individuals at a specific point in time, providing a snapshot of the population being studied.
• Longitudinal survey: A type of survey research that gathers data from the same sample of individuals over an extended period of time, allowing researchers to track changes or trends in the population being studied.
• Panel survey: A type of longitudinal survey research that tracks the same sample of individuals over time, typically collecting data at multiple points in time.
• Epidemiological survey: A type of survey research that studies the distribution and determinants of health and disease in a population, often used to identify risk factors and inform public health interventions.
• Observational survey: A type of survey research that collects data through direct observation of individuals or groups, often used in behavioral or social research.
• Correlational survey: A type of survey research that measures the degree of association or relationship between two or more variables, often used to identify patterns or trends in data.
• Experimental survey: A type of survey research that involves manipulating one or more variables to observe the effect on an outcome, often used to test causal hypotheses.
• Descriptive survey: A type of survey research that describes the characteristics or attributes of a population or phenomenon, often used in exploratory research or to summarize existing data.
• Diagnostic survey: A type of survey research that assesses the current state or condition of an individual or system, often used in health or organizational research.
• Explanatory survey: A type of survey research that seeks to explain or understand the causes or mechanisms behind a phenomenon, often used in social or psychological research.
• Process evaluation survey: A type of survey research that measures the implementation and outcomes of a program or intervention, often used in program evaluation or quality improvement.
• Impact evaluation survey: A type of survey research that assesses the effectiveness or impact of a program or intervention, often used to inform policy or decision-making.
• Customer satisfaction survey: A type of survey research that measures the satisfaction or dissatisfaction of customers with a product, service, or experience, often used in marketing or customer service research.
• Market research survey: A type of survey research that collects data on consumer preferences, behaviors, or attitudes, often used in market research or product development.
• Public opinion survey: A type of survey research that measures the attitudes, beliefs, or opinions of a population on a specific issue or topic, often used in political or social research.
• Behavioral survey: A type of survey research that measures actual behavior or actions of individuals, often used in health or social research.
• Attitude survey: A type of survey research that measures the attitudes, beliefs, or opinions of individuals, often used in social or psychological research.
• Opinion poll: A type of survey research that measures the opinions or preferences of a population on a specific issue or topic, often used in political or media research.
• Ad hoc survey: A type of survey research that is conducted for a specific purpose or research question, often used in exploratory research or to answer a specific research question.

Types Based on Methodology

Based on Methodology Survey are divided into two Types:

Quantitative Survey Research

Qualitative survey research.

Quantitative survey research is a method of collecting numerical data from a sample of participants through the use of standardized surveys or questionnaires. The purpose of quantitative survey research is to gather empirical evidence that can be analyzed statistically to draw conclusions about a particular population or phenomenon.

In quantitative survey research, the questions are structured and pre-determined, often utilizing closed-ended questions, where participants are given a limited set of response options to choose from. This approach allows for efficient data collection and analysis, as well as the ability to generalize the findings to a larger population.

Quantitative survey research is often used in market research, social sciences, public health, and other fields where numerical data is needed to make informed decisions and recommendations.

Qualitative survey research is a method of collecting non-numerical data from a sample of participants through the use of open-ended questions or semi-structured interviews. The purpose of qualitative survey research is to gain a deeper understanding of the experiences, perceptions, and attitudes of participants towards a particular phenomenon or topic.

In qualitative survey research, the questions are open-ended, allowing participants to share their thoughts and experiences in their own words. This approach allows for a rich and nuanced understanding of the topic being studied, and can provide insights that are difficult to capture through quantitative methods alone.

Qualitative survey research is often used in social sciences, education, psychology, and other fields where a deeper understanding of human experiences and perceptions is needed to inform policy, practice, or theory.

Data Analysis Methods

There are several Survey Research Data Analysis Methods that researchers may use, including:

• Descriptive statistics: This method is used to summarize and describe the basic features of the survey data, such as the mean, median, mode, and standard deviation. These statistics can help researchers understand the distribution of responses and identify any trends or patterns.
• Inferential statistics: This method is used to make inferences about the larger population based on the data collected in the survey. Common inferential statistical methods include hypothesis testing, regression analysis, and correlation analysis.
• Factor analysis: This method is used to identify underlying factors or dimensions in the survey data. This can help researchers simplify the data and identify patterns and relationships that may not be immediately apparent.
• Cluster analysis: This method is used to group similar respondents together based on their survey responses. This can help researchers identify subgroups within the larger population and understand how different groups may differ in their attitudes, behaviors, or preferences.
• Structural equation modeling: This method is used to test complex relationships between variables in the survey data. It can help researchers understand how different variables may be related to one another and how they may influence one another.
• Content analysis: This method is used to analyze open-ended responses in the survey data. Researchers may use software to identify themes or categories in the responses, or they may manually review and code the responses.
• Text mining: This method is used to analyze text-based survey data, such as responses to open-ended questions. Researchers may use software to identify patterns and themes in the text, or they may manually review and code the text.

Applications of Survey Research

Here are some common applications of survey research:

• Market Research: Companies use survey research to gather insights about customer needs, preferences, and behavior. These insights are used to create marketing strategies and develop new products.
• Public Opinion Research: Governments and political parties use survey research to understand public opinion on various issues. This information is used to develop policies and make decisions.
• Social Research: Survey research is used in social research to study social trends, attitudes, and behavior. Researchers use survey data to explore topics such as education, health, and social inequality.
• Academic Research: Survey research is used in academic research to study various phenomena. Researchers use survey data to test theories, explore relationships between variables, and draw conclusions.
• Customer Satisfaction Research: Companies use survey research to gather information about customer satisfaction with their products and services. This information is used to improve customer experience and retention.
• Employee Surveys: Employers use survey research to gather feedback from employees about their job satisfaction, working conditions, and organizational culture. This information is used to improve employee retention and productivity.
• Health Research: Survey research is used in health research to study topics such as disease prevalence, health behaviors, and healthcare access. Researchers use survey data to develop interventions and improve healthcare outcomes.

Examples of Survey Research

Here are some real-time examples of survey research:

• COVID-19 Pandemic Surveys: Since the outbreak of the COVID-19 pandemic, surveys have been conducted to gather information about public attitudes, behaviors, and perceptions related to the pandemic. Governments and healthcare organizations have used this data to develop public health strategies and messaging.
• Political Polls During Elections: During election seasons, surveys are used to measure public opinion on political candidates, policies, and issues in real-time. This information is used by political parties to develop campaign strategies and make decisions.
• Customer Feedback Surveys: Companies often use real-time customer feedback surveys to gather insights about customer experience and satisfaction. This information is used to improve products and services quickly.
• Event Surveys: Organizers of events such as conferences and trade shows often use surveys to gather feedback from attendees in real-time. This information can be used to improve future events and make adjustments during the current event.
• Website and App Surveys: Website and app owners use surveys to gather real-time feedback from users about the functionality, user experience, and overall satisfaction with their platforms. This feedback can be used to improve the user experience and retain customers.
• Employee Pulse Surveys: Employers use real-time pulse surveys to gather feedback from employees about their work experience and overall job satisfaction. This feedback is used to make changes in real-time to improve employee retention and productivity.

Survey Sample

Purpose of survey research.

The purpose of survey research is to gather data and insights from a representative sample of individuals. Survey research allows researchers to collect data quickly and efficiently from a large number of people, making it a valuable tool for understanding attitudes, behaviors, and preferences.

Here are some common purposes of survey research:

• Descriptive Research: Survey research is often used to describe characteristics of a population or a phenomenon. For example, a survey could be used to describe the characteristics of a particular demographic group, such as age, gender, or income.
• Exploratory Research: Survey research can be used to explore new topics or areas of research. Exploratory surveys are often used to generate hypotheses or identify potential relationships between variables.
• Explanatory Research: Survey research can be used to explain relationships between variables. For example, a survey could be used to determine whether there is a relationship between educational attainment and income.
• Evaluation Research: Survey research can be used to evaluate the effectiveness of a program or intervention. For example, a survey could be used to evaluate the impact of a health education program on behavior change.
• Monitoring Research: Survey research can be used to monitor trends or changes over time. For example, a survey could be used to monitor changes in attitudes towards climate change or political candidates over time.

When to use Survey Research

there are certain circumstances where survey research is particularly appropriate. Here are some situations where survey research may be useful:

• When the research question involves attitudes, beliefs, or opinions: Survey research is particularly useful for understanding attitudes, beliefs, and opinions on a particular topic. For example, a survey could be used to understand public opinion on a political issue.
• When the research question involves behaviors or experiences: Survey research can also be useful for understanding behaviors and experiences. For example, a survey could be used to understand the prevalence of a particular health behavior.
• When a large sample size is needed: Survey research allows researchers to collect data from a large number of people quickly and efficiently. This makes it a useful method when a large sample size is needed to ensure statistical validity.
• When the research question is time-sensitive: Survey research can be conducted quickly, which makes it a useful method when the research question is time-sensitive. For example, a survey could be used to understand public opinion on a breaking news story.
• When the research question involves a geographically dispersed population: Survey research can be conducted online, which makes it a useful method when the population of interest is geographically dispersed.

How to Conduct Survey Research

Conducting survey research involves several steps that need to be carefully planned and executed. Here is a general overview of the process:

• Define the research question: The first step in conducting survey research is to clearly define the research question. The research question should be specific, measurable, and relevant to the population of interest.
• Develop a survey instrument : The next step is to develop a survey instrument. This can be done using various methods, such as online survey tools or paper surveys. The survey instrument should be designed to elicit the information needed to answer the research question, and should be pre-tested with a small sample of individuals.
• Select a sample : The sample is the group of individuals who will be invited to participate in the survey. The sample should be representative of the population of interest, and the size of the sample should be sufficient to ensure statistical validity.
• Administer the survey: The survey can be administered in various ways, such as online, by mail, or in person. The method of administration should be chosen based on the population of interest and the research question.
• Analyze the data: Once the survey data is collected, it needs to be analyzed. This involves summarizing the data using statistical methods, such as frequency distributions or regression analysis.
• Draw conclusions: The final step is to draw conclusions based on the data analysis. This involves interpreting the results and answering the research question.

Advantages of Survey Research

There are several advantages to using survey research, including:

• Efficient data collection: Survey research allows researchers to collect data quickly and efficiently from a large number of people. This makes it a useful method for gathering information on a wide range of topics.
• Standardized data collection: Surveys are typically standardized, which means that all participants receive the same questions in the same order. This ensures that the data collected is consistent and reliable.
• Cost-effective: Surveys can be conducted online, by mail, or in person, which makes them a cost-effective method of data collection.
• Anonymity: Participants can remain anonymous when responding to a survey. This can encourage participants to be more honest and open in their responses.
• Easy comparison: Surveys allow for easy comparison of data between different groups or over time. This makes it possible to identify trends and patterns in the data.
• Versatility: Surveys can be used to collect data on a wide range of topics, including attitudes, beliefs, behaviors, and preferences.

Limitations of Survey Research

Here are some of the main limitations of survey research:

• Limited depth: Surveys are typically designed to collect quantitative data, which means that they do not provide much depth or detail about people’s experiences or opinions. This can limit the insights that can be gained from the data.
• Potential for bias: Surveys can be affected by various biases, including selection bias, response bias, and social desirability bias. These biases can distort the results and make them less accurate.
• L imited validity: Surveys are only as valid as the questions they ask. If the questions are poorly designed or ambiguous, the results may not accurately reflect the respondents’ attitudes or behaviors.
• Limited generalizability : Survey results are only generalizable to the population from which the sample was drawn. If the sample is not representative of the population, the results may not be generalizable to the larger population.
• Limited ability to capture context: Surveys typically do not capture the context in which attitudes or behaviors occur. This can make it difficult to understand the reasons behind the responses.
• Limited ability to capture complex phenomena: Surveys are not well-suited to capture complex phenomena, such as emotions or the dynamics of interpersonal relationships.

Following is an example of a Survey Sample:

Welcome to our Survey Research Page! We value your opinions and appreciate your participation in this survey. Please answer the questions below as honestly and thoroughly as possible.

1. What is your age?

• A) Under 18
• G) 65 or older

2. What is your highest level of education completed?

• A) Less than high school
• B) High school or equivalent
• C) Some college or technical school
• D) Bachelor’s degree
• E) Graduate or professional degree

3. What is your current employment status?

• A) Employed full-time
• B) Employed part-time
• C) Self-employed
• D) Unemployed

4. How often do you use the internet per day?

•  A) Less than 1 hour
• B) 1-3 hours
• C) 3-5 hours
• D) 5-7 hours
• E) More than 7 hours

5. How often do you engage in social media per day?

6. Have you ever participated in a survey research study before?

7. If you have participated in a survey research study before, how was your experience?

• A) Excellent
• E) Very poor

8. What are some of the topics that you would be interested in participating in a survey research study about?

……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….

9. How often would you be willing to participate in survey research studies?

• A) Once a week
• B) Once a month
• C) Once every 6 months
• D) Once a year

10. Any additional comments or suggestions?

Thank you for taking the time to complete this survey. Your feedback is important to us and will help us improve our survey research efforts.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• Survey Research: Types, Examples & Methods

Surveys have been proven to be one of the most effective methods of conducting research. They help you to gather relevant data from a large audience, which helps you to arrive at a valid and objective conclusion. 

Just like other research methods, survey research had to be conducted the right way to be effective. In this article, we’ll dive into the nitty-gritty of survey research and show you how to get the most out of it. 

What is Survey Research? 

Survey research is simply a systematic investigation conducted via a survey. In other words, it is a type of research carried out by administering surveys to respondents. 

Surveys already serve as a great method of opinion sampling and finding out what people think about different contexts and situations. Applying this to research means you can gather first-hand information from persons affected by specific contexts. 

Survey research proves useful in numerous primary research scenarios. Consider the case whereby a restaurant wants to gather feedback from its customers on its new signatory dish. A good way to do this is to conduct survey research on a defined customer demographic. 

By doing this, the restaurant is better able to gather primary data from the customers (respondents) with regards to what they think and feel about the new dish across multiple facets. This means they’d have more valid and objective information to work with. 

Why Conduct Survey Research?  

One of the strongest arguments for survey research is that it helps you gather the most authentic data sets in the systematic investigation. Survey research is a gateway to collecting specific information from defined respondents, first-hand.  

Surveys combine different question types that make it easy for you to collect numerous information from respondents. When you come across a questionnaire for survey research, you’re likely to see a neat blend of close-ended and open-ended questions, together with other survey response scale questions. 

Apart from what we’ve discussed so far, here are some other reasons why survey research is important: 

• It gives you insights into respondents’ behaviors and preferences which is valid in any systematic investigation.
• Many times, survey research is structured in an interactive manner which makes it easier for respondents to communicate their thoughts and experiences. 
• It allows you to gather important data that proves useful for product improvement; especially in market research. 

Characteristics of Survey Research

• Usage : Survey research is mostly deployed in the field of social science; especially to gather information about human behavior in different social contexts. 
• Systematic : Like other research methods, survey research is systematic. This means that it is usually conducted in line with empirical methods and follows specific processes.
• Replicable : In survey research, applying the same methods often translates to achieving similar results. 
• Types : Survey research can be conducted using forms (offline and online) or via structured, semi-structured, and unstructured interviews . 
• Data : The data gathered from survey research is mostly quantitative; although it can be qualitative. 
• Impartial Sampling : The data sample in survey research is random and not subject to unavoidable biases.
• Ecological Validity : Survey research often makes use of data samples obtained from real-world occurrences. 

Types of Survey Research

Survey research can be subdivided into different types based on its objectives, data source, and methodology. 

Types of Survey Research Based on Objective

• Exploratory Survey Research

Exploratory survey research is aimed at finding out more about the research context. Here, the survey research pays attention to discovering new ideas and insights about the research subject(s) or contexts. 

Exploratory survey research is usually made up of open-ended questions that allow respondents to fully communicate their thoughts and varying perspectives on the subject matter. In many cases, systematic investigation kicks off with an exploratory research survey. 

• Predictive Survey Research

This type of research is also referred to as causal survey research because it pays attention to the causative relationship between the variables in the survey research. In other words, predictive survey research pays attention to existing patterns to explain the relationship between two variables. 

It can also be referred to as conclusive research because it allows you to identify causal variables and resultant variables; that is cause and effect. Predictive variables allow you to determine the nature of the relationship between the causal variables and the effect to be predicted. 

• Descriptive Survey Research

Unlike predictive research, descriptive survey research is largely observational. It is ideal for quantitative research because it helps you to gather numeric data. 

The questions listed in descriptive survey research help you to uncover new insights into the actions, thoughts, and feelings of survey respondents. With this data, you can know the extent to which different conditions can be obtained among these subjects. 

Types of Survey Research Based on Data Source

• Secondary Data

Survey research can be designed to collect and process secondary data. Secondary data is a type of data that has been collected from primary sources in the past and is readily available for use. It is the type of data that is already existing.

Since secondary data is gathered from third-party sources, it is mostly generic, unlike primary data that is specific to the research context. Common sources of secondary data in survey research include books, data collected through other surveys, online data, data from government archives, and libraries. 

• Primary Data

This is the type of research data that is collected directly; that is, data collected from first-hand sources. Primary data is usually tailored to a specific research context so that reflects the aims and objectives of the systematic investigation.

One of the strongest points of primary data over its secondary counterpart is validity. Because it is collected directly from first-hand sources, primary data typically results in objective research findings. 

You can collect primary data via interviews, surveys, and questionnaires, and observation methods. 

Types of Survey Research Based on Methodology

• Quantitative Research

Quantitative research is a common research method that is used to gather numerical data in a systematic investigation. It is often deployed in research contexts that require statistical information to arrive at valid results such as in social science or science. 

For instance, as an organization looking to find out how many persons are using your product in a particular location, you can administer survey research to collect useful quantitative data. Other quantitative research methods include polls, face-to-face interviews, and systematic observation. 

• Qualitative Research

This is a method of systematic investigation that is used to collect non-numerical data from research participants. In other words, it is a research method that allows you to gather open-ended information from your target audience. 

Typically, organizations deploy qualitative research methods when they need to gather descriptive data from their customers; for example, when they need to collect customer feedback in product evaluation. Qualitative research methods include one-on-one interviews, observation, case studies, and focus groups. 

Survey Research Scales

• Nominal Scale

This is a type of survey research scale that uses numbers to label the different answer options in a survey. On a nominal scale , the numbers have no value in themselves; they simply serve as labels for qualitative variables in the survey. 

In cases where a nominal scale is used for identification, there is typically a specific one-on-one relationship between the numeric value and the variable it represents. On the other hand, when the variable is used for classification, then each number on the scale serves as a label or a tag. 

Examples of Nominal Scale in Survey Research 

1. How would you describe your complexion? 

2. Have you used this product?

• Ordinal Scale

This is a type of variable measurement scale that arranges answer options in a specific ranking order without necessarily indicating the degree of variation between these options. Ordinal data is qualitative and can be named, ranked, or grouped. 

In an ordinal scale , the different properties of the variables are relatively unknown, and it also identifies, describes, and shows the rank of the different variables. With an ordered scale, it is easier for researchers to measure the degree of agreement and/or disagreement with different variables. 

With ordinal scales, you can measure non-numerical attributes such as the degree of happiness, agreement, or opposition of respondents in specific contexts. Using an ordinal scale makes it easy for you to compare variables and process survey responses accordingly. 

Examples of Ordinal Scale in Survey Research

1. How often do you use this product?

• Prefer not to say

2. How much do you agree with our new policies? 

• Totally agree
• Somewhat agree
• Totally disagree
• Interval Scale

This is a type of survey scale that is used to measure variables existing at equal intervals along a common scale. In some way, it combines the attributes of nominal and ordinal scales since it is used where there is order and there is a meaningful difference between 2 variables. 

With an interval scale, you can quantify the difference in value between two variables in survey research. In addition to this, you can carry out other mathematical processes like calculating the mean and median of research variables. 

Examples of Interval Scale in Survey Research

1. Our customer support team was very effective. 

• Completely agree
• Neither agree nor disagree
• Somewhat disagree
• Completely disagree 

2. I enjoyed using this product.

Another example of an interval scale can be seen in the Net Promoter Score.

• Ratio Scale

Just like the interval scale, the ratio scale is quantitative and it is used when you need to compare intervals or differences in survey research. It is the highest level of measurement and it is made up of bits and pieces of the other survey scales. 

One of the unique features of the ratio scale is it has a true zero and equal intervals between the variables on the scale. This zero indicates an absence of the variable being measured by the scale. Common occurrences of ratio scales can be seen with distance (length), area, and population measurement. 

Examples of Ratio Scale in Survey Research

1. How old are you?

• Below 18 years
• 41 and above

2. How many times do you shop in a week?

• Less than twice
• Three times
• More than four times

Uses of Survey Research

• Health Surveys

Survey research is used by health practitioners to gather useful data from patients in different medical and safety contexts. It helps you to gather primary and secondary data about medical conditions and risk factors of multiple diseases and infections. 

In addition to this, administering health surveys regularly helps you to monitor the overall health status of your population; whether in the workplace, school, or community. This kind of data can be used to help prevent outbreaks and minimize medical emergencies in these contexts. 

Survey research is also useful when conducting polls; whether online or offline. A poll is a data collection tool that helps you to gather public opinion about a particular subject from a well-defined research sample.

By administering survey research, you can gather valid data from a well-defined research sample, and utilize research findings for decision making. For example, during elections, individuals can be asked to choose their preferred leader via questionnaires administered as part of survey research.

• Customer Satisfaction

Customer satisfaction is one of the cores of every organization as it is directly concerned with how well your product or service meets the needs of your clients. Survey research is an effective way to measure customer satisfaction at different intervals. 

As a restaurant, for example, you can send out online surveys to customers immediately when they patronize your business. In these surveys, encourage them to provide feedback on their experience and to provide information on how your service delivery can be improved. 

Survey research makes data collection and analysis easy during a census. With an online survey tool like Formplus , you can seamlessly gather data during a census without moving from a spot. Formplus has multiple sharing options that help you collect information without stress. 

Survey Research Methods

Survey research can be done using different online and offline methods. Let’s examine a few of them here.

• Telephone Surveys

This is a means of conducting survey research via phone calls. In a telephone survey, the researcher places a call to the survey respondents and gathers information from them by asking questions about the research context under consideration. 

A telephone survey is a kind of simulation of the face-to-face survey experience since it involves discussing with respondents to gather and process valid data. However, major challenges with this method include the fact that it is expensive and time-consuming. 

• Online Surveys

An online survey is a data collection tool used to create and administer surveys and questionnaires using data tools like Formplus. Online surveys work better than paper forms and other offline survey methods because you can easily gather and process data from a large sample size with them. 

• Face-to-Face Interviews

Face-to-face interviews for survey research can be structured, semi-structured, or unstructured depending on the research context and the type of data you want to collect. If you want to gather qualitative data , then unstructured and semi-structured interviews are the way to go. 

On the other hand, if you want to collect quantifiable information from your research sample, conducting a structured interview is the best way to go. Face-to-face interviews can also be time-consuming and cost-intensive. Let’s mention here that face-to-face surveys are one of the most widely used methods of survey data collection. 

How to Conduct Research Surveys on Formplus 

With Formplus, you can create forms for survey research without any hassles. Follow this step-by-step guide to create and administer online surveys for research via Formplus. 

1. Sign up at www.formpl.us to create your Formplus account. If you already have a Formplus account, click here to log in.

5. Use the form customization options to change the appearance of your survey. You can add your organization’s logo to the survey, change the form font and layout, and insert preferred background images.

Advantages of Survey Research

• It is inexpensive – with survey research, you can avoid the cost of in-person interviews. It’s also easy to receive data as you can share your surveys online and get responses from a large demographic
• It is the fastest way to get a large amount of first-hand data
• Surveys allow you to compare the results you get through charts and graphs
• It is versatile as it can be used for any research topic
• Surveys are perfect for anonymous respondents in the research 

Disadvantages of Survey Research

• Some questions may not get answers
• People may understand survey questions differently
• It may not be the best option for respondents with visual or hearing impairments as well as a demographic with no literacy levels
• People can provide dishonest answers in a survey research

Conclusion 

In this article, we’ve discussed survey research extensively; touching on different important aspects of this concept. As a researcher, organization, individual, or student, it is important to understand how survey research works to utilize it effectively and get the most from this method of systematic investigation. 

As we’ve already stated, conducting survey research online is one of the most effective methods of data collection as it allows you to gather valid data from a large group of respondents. If you’re looking to kick off your survey research, you can start by signing up for a Formplus account here. 

Connect to Formplus, Get Started Now - It's Free!

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• Doing Survey Research | A Step-by-Step Guide & Examples

Doing Survey Research | A Step-by-Step Guide & Examples

Published on 6 May 2022 by Shona McCombes . Revised on 10 October 2022.

Survey research means collecting information about a group of people by asking them questions and analysing the results. To conduct an effective survey, follow these six steps:

• Determine who will participate in the survey
• Decide the type of survey (mail, online, or in-person)
• Design the survey questions and layout
• Distribute the survey
• Analyse the responses
• Write up the results

Surveys are a flexible method of data collection that can be used in many different types of research .

Table of contents

What are surveys used for, step 1: define the population and sample, step 2: decide on the type of survey, step 3: design the survey questions, step 4: distribute the survey and collect responses, step 5: analyse the survey results, step 6: write up the survey results, frequently asked questions about surveys.

Surveys are used as a method of gathering data in many different fields. They are a good choice when you want to find out about the characteristics, preferences, opinions, or beliefs of a group of people.

Common uses of survey research include:

• Social research: Investigating the experiences and characteristics of different social groups
• Market research: Finding out what customers think about products, services, and companies
• Health research: Collecting data from patients about symptoms and treatments
• Politics: Measuring public opinion about parties and policies
• Psychology: Researching personality traits, preferences, and behaviours

Surveys can be used in both cross-sectional studies , where you collect data just once, and longitudinal studies , where you survey the same sample several times over an extended period.

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Before you start conducting survey research, you should already have a clear research question that defines what you want to find out. Based on this question, you need to determine exactly who you will target to participate in the survey.

Populations

The target population is the specific group of people that you want to find out about. This group can be very broad or relatively narrow. For example:

• The population of Brazil
• University students in the UK
• Second-generation immigrants in the Netherlands
• Customers of a specific company aged 18 to 24
• British transgender women over the age of 50

Your survey should aim to produce results that can be generalised to the whole population. That means you need to carefully define exactly who you want to draw conclusions about.

It’s rarely possible to survey the entire population of your research – it would be very difficult to get a response from every person in Brazil or every university student in the UK. Instead, you will usually survey a sample from the population.

The sample size depends on how big the population is. You can use an online sample calculator to work out how many responses you need.

There are many sampling methods that allow you to generalise to broad populations. In general, though, the sample should aim to be representative of the population as a whole. The larger and more representative your sample, the more valid your conclusions.

There are two main types of survey:

• A questionnaire , where a list of questions is distributed by post, online, or in person, and respondents fill it out themselves
• An interview , where the researcher asks a set of questions by phone or in person and records the responses

Which type you choose depends on the sample size and location, as well as the focus of the research.

Questionnaires

Sending out a paper survey by post is a common method of gathering demographic information (for example, in a government census of the population).

• You can easily access a large sample.
• You have some control over who is included in the sample (e.g., residents of a specific region).
• The response rate is often low.

Online surveys are a popular choice for students doing dissertation research , due to the low cost and flexibility of this method. There are many online tools available for constructing surveys, such as SurveyMonkey and Google Forms .

• You can quickly access a large sample without constraints on time or location.
• The data is easy to process and analyse.
• The anonymity and accessibility of online surveys mean you have less control over who responds.

If your research focuses on a specific location, you can distribute a written questionnaire to be completed by respondents on the spot. For example, you could approach the customers of a shopping centre or ask all students to complete a questionnaire at the end of a class.

• You can screen respondents to make sure only people in the target population are included in the sample.
• You can collect time- and location-specific data (e.g., the opinions of a shop’s weekday customers).
• The sample size will be smaller, so this method is less suitable for collecting data on broad populations.

Oral interviews are a useful method for smaller sample sizes. They allow you to gather more in-depth information on people’s opinions and preferences. You can conduct interviews by phone or in person.

• You have personal contact with respondents, so you know exactly who will be included in the sample in advance.
• You can clarify questions and ask for follow-up information when necessary.
• The lack of anonymity may cause respondents to answer less honestly, and there is more risk of researcher bias.

Like questionnaires, interviews can be used to collect quantitative data : the researcher records each response as a category or rating and statistically analyses the results. But they are more commonly used to collect qualitative data : the interviewees’ full responses are transcribed and analysed individually to gain a richer understanding of their opinions and feelings.

Next, you need to decide which questions you will ask and how you will ask them. It’s important to consider:

• The type of questions
• The content of the questions
• The phrasing of the questions
• The ordering and layout of the survey

Open-ended vs closed-ended questions

There are two main forms of survey questions: open-ended and closed-ended. Many surveys use a combination of both.

Closed-ended questions give the respondent a predetermined set of answers to choose from. A closed-ended question can include:

• A binary answer (e.g., yes/no or agree/disagree )
• A scale (e.g., a Likert scale with five points ranging from strongly agree to strongly disagree )
• A list of options with a single answer possible (e.g., age categories)
• A list of options with multiple answers possible (e.g., leisure interests)

Closed-ended questions are best for quantitative research . They provide you with numerical data that can be statistically analysed to find patterns, trends, and correlations .

Open-ended questions are best for qualitative research. This type of question has no predetermined answers to choose from. Instead, the respondent answers in their own words.

Open questions are most common in interviews, but you can also use them in questionnaires. They are often useful as follow-up questions to ask for more detailed explanations of responses to the closed questions.

The content of the survey questions

To ensure the validity and reliability of your results, you need to carefully consider each question in the survey. All questions should be narrowly focused with enough context for the respondent to answer accurately. Avoid questions that are not directly relevant to the survey’s purpose.

When constructing closed-ended questions, ensure that the options cover all possibilities. If you include a list of options that isn’t exhaustive, you can add an ‘other’ field.

Phrasing the survey questions

In terms of language, the survey questions should be as clear and precise as possible. Tailor the questions to your target population, keeping in mind their level of knowledge of the topic.

Use language that respondents will easily understand, and avoid words with vague or ambiguous meanings. Make sure your questions are phrased neutrally, with no bias towards one answer or another.

Ordering the survey questions

The questions should be arranged in a logical order. Start with easy, non-sensitive, closed-ended questions that will encourage the respondent to continue.

If the survey covers several different topics or themes, group together related questions. You can divide a questionnaire into sections to help respondents understand what is being asked in each part.

If a question refers back to or depends on the answer to a previous question, they should be placed directly next to one another.

Before you start, create a clear plan for where, when, how, and with whom you will conduct the survey. Determine in advance how many responses you require and how you will gain access to the sample.

When you are satisfied that you have created a strong research design suitable for answering your research questions, you can conduct the survey through your method of choice – by post, online, or in person.

There are many methods of analysing the results of your survey. First you have to process the data, usually with the help of a computer program to sort all the responses. You should also cleanse the data by removing incomplete or incorrectly completed responses.

If you asked open-ended questions, you will have to code the responses by assigning labels to each response and organising them into categories or themes. You can also use more qualitative methods, such as thematic analysis , which is especially suitable for analysing interviews.

Statistical analysis is usually conducted using programs like SPSS or Stata. The same set of survey data can be subject to many analyses.

Finally, when you have collected and analysed all the necessary data, you will write it up as part of your thesis, dissertation , or research paper .

In the methodology section, you describe exactly how you conducted the survey. You should explain the types of questions you used, the sampling method, when and where the survey took place, and the response rate. You can include the full questionnaire as an appendix and refer to it in the text if relevant.

Then introduce the analysis by describing how you prepared the data and the statistical methods you used to analyse it. In the results section, you summarise the key results from your analysis.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyse your data.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

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• Understanding the 3 Main Types of Survey Research & Putting Them to Use

Understanding the 3 Main Types of Survey Research & Putting Them to Use

Surveys establish a powerful primary source of market research. There are three main types of survey research; understanding these will not merely organize your survey studies, but help you form them from the onset of your research campaign.

It is crucial to be proficient in these types of survey research, as surveys should never be used as lone tools. A survey is a vehicle for granting insights, as part of a larger market research or other research campaigns. 

Understanding the three types of survey research will help you learn aspects within these forms that you were either not aware of or were not well-versed in.

This article explores the three main types of survey research and teaches you when to best implement each form of research. 

Putting the Types of Survey Research into Perspective 

With the presence of online surveys and other market research methods such as focus groups , there are ever-growing survey research methods . Before you choose a method, it is critical to decide on the type of survey research you need to conduct.

The type of survey research points to the kind of study you are going to apply in your campaign and all of its implications . The survey research type essentially hosts the research methods, which house the actual surveys . As such, the research type is one of the highest levels of the process, so consider it as a starting point in your research campaign.

Remember, that while there are various research types, the three presented in this article delineate the main types used in survey research. Researchers can apply these types to other research techniques (such as focus groups, interviews, etc.), but they are best suited for surveys.

Descriptive Research

The first main type of survey research is descriptive research. This type is centered on describing, as its name suggests, a topic of study. This can be a population, an occurrence or a phenomenon. 

Descriptive research is often the first type of research applied around a research issue, because it paints a picture of a topic, rather than investigating why it exists to begin with. 

The Key Aspects of Descriptive Research

The following provides the key attributes of descriptive research, so as to provide a full understanding of it.

• Makes up the majority of online survey methods.
• Concentrates on the what, when, where and how questions, rather than the why.
• Lays out the particulars surrounding a research topic, but not its origin.
• Handles quantitative studies.
• Deemed conclusive due to its quantitative data.
• Provides data that provides statistical inferences on a target population.
• Preplanned and highly structured.
• Aims to define an occurrence, attitude or opinions of the studied population.
• Measures the significance of the results and formulates trends.
• Can be used in cross-sectional and longitudinal surveys.

Survey Examples of Descriptive Research 

There are various types of surveys to use for descriptive research. In fact, you can apply virtually all of them if they meet the above requirements. Here are the major ones:

• Descriptive surveys: These gather data about different subjects. They are set to find how different conditions can be gained by the subjects and the extent thereof. Ex: determining how qualified applicants are to a job are via a survey checking for this.
• Descriptive-normative surveys: Much like descriptive surveys, but the results of the survey are compared with a norm. 
• Descriptive analysis surveys: This survey describes a phenomenon via an analysis that divides the subject into 2 parts. Ex: analyzing employees with the same job role across geolocations. 
• Correlative Survey: This determines whether the relationship between 2 variables is either positive or negative; sometimes it can be used to find neutrality. For example, if A and B have negative, positive or no correlation.

Exploratory Research 

Exploratory research is predicated on unearthing ideas and insights rather than amassing statistics. Also unlike descriptive research, exploratory research is not conclusive. This is because this research is conducted to obtain a better understanding of an existing phenomenon, one that has either not been studied thoroughly or is lacking some information.

Exploratory research is most apt to use at the beginning of a research campaign. In business, this kind of research is necessary for identifying issues within a company, opportunities for growth, adopting new procedures and deciding on which issues require statistical research, i.e., descriptive research. 

The Key Aspects of Exploratory Research

Also called interpretative research or grounded theory approach, the following provides the key attributes of exploratory research, including how it differs from descriptive research. 

• Uses exploratory questions, which are intended to probe subjects in a qualitative manner.
• Provides quality information that can uncover other unknown issues or solutions.
• Is not meant to provide data that is statistically measurable. 
• Used to get a familiarity with an existing problem by understanding its specifics.
• Starts with a general idea with the outcomes of the research being used to find related issues with the research subject.
• Typically exists within open-ended questions.  
• Its process varies based on the new insights researchers gain and how they choose to go about them.
• Usually asks for the what, how and most distinctively, the why.
• Due to the absence of past research on the subject, exploratory research is time-consuming,
• Not structured and flexible.

Examples of Exploratory Research

Since exploratory research is not structured and often scattered, it can exist within a multitude of survey types. For example, it can be used in an employee feedback survey, a cross-sectional survey and virtually any other that allows you to ask questions on the why and employs open-ended questions. 

Here are a few other ways to conduct exploratory research:

• Case studies: They help researchers analyze existing cases that deal with a similar phenomenon. This method often involves secondary research , unless your business or organization has case studies on a similar topic. Perhaps one of your competitors offers one as well. With case studies, the researcher needs to study all the variables in the case study in relation to their own. 
• Field Observations: This method is best suited for researchers who deal with their subjects in physical environments, for example, those studying customers in a store or patients in a clinic. It can also be applied by studying digital behaviors using a session replay tool. 
• Focus Groups: This involves a group of people, typically 6-10 coming together and speaking with the researcher, as opposed to having a one on one conversation with the researcher. Participants are chosen to provide insights on the topic of study and express it with other members of the focus group, while the researcher observes and acts as a moderator. 
• Interviews : Interviews can be conducted in person or over the phone. Researchers have the option of interviewing their target market, their overall target population, or subject matter experts. The latter will provide significant and professional-grade insights, the kind that non-experts typically can’t offer. 

Causal Research

The final type of survey research is causal research, which, much like descriptive research is structured, preplanned and draws quantitative insights. Also called explanatory research, causal research aims to discover whether there is any causality between the relationships of variables. 

As such, focuses primarily on cause-and-effect relationships. In this regard, it stands in opposition with descriptive research, which is far broader. Causal research has only two objects:

• Understand which variable are the cause and which are the effect
• Decipher the workings of the relationship between the causal variables, including how they will hammer out the effect.

The Key Aspects of Causal Research

The following provides the key traits of causal research, including how it differs from descriptive and exploratory research. 

• Considered conclusive research due to its structured design, preplanning and quantitative nature. 
• Its two objectives make this research type more scientific than exploratory and descriptive research. 
• Focuses on observing the variations in variables suspected as causing the changes in other variables.
• Measure changes in both the suspected causal variables and the ones they affect.
• Variables suspected of being causal are isolated and tested to meet the aforesaid two objectives.
• For example, an advertisement or a sales promotion
• Requires setting objectives, preplanning parameters, and identifying potential causal variables and affected variables to reduce researcher bias. 
• Requires accounting for all the possible causal factors that may be affecting the supposed affected variable, i.e., there can’t be any outside (non-accounted) variables.
• All confounding variables that can affect the results have to be kept consistent and controlled to make sure no hidden variable is in any way influencing the relationship between two variables. 
• To deem a cause and effect relationship, the cause would have needed to precede the effect.  

Examples of Causal Research

Causal research depends on the most scientific method out of the three types of survey research. Given that it requires experimentation, a vast amount of surveys can be conducted on the variables to determine if they are causal, non-causal or the ones being affected.

Here are a few examples of use causal research

• Product testing: Particularly useful if it’s a new product to test market demand and sales capacity. 
• Advertising Improvements: Researchers can study buying behaviors to see if there is any causality between ads and how much people buy or if the advertised products reach higher sales. The outcomes of this research can help marketers tweak their ad campaigns, discard them altogether or even consider product updates.
• Increase customer retention : This can be conducted in different manners, such as via in-store experimentations, via digital shopping or through different surveys. These experiments will help you understand what current customers prefer and what repels them. 
• Community Needs : Local governments can conduct the community survey to discover opinions surrounding community issues. For example, researchers can test whether certain local laws, transportation availability and authorizations are well or poorly received and if they correlate with certain happenings.

Deciding on Which of the Types of Research to Conduct

Market researchers and marketers often have several aspects of their discipline that would benefit off of conducting these three types of survey research. What’s most empowering about these types of survey research is that they are not limited to surveys alone.

Instead, they bolster the idea that surveys should not be used as lone tools. Rather, survey research powers an abundance of other market research methods and campaigns. As such, researchers should set aside surveys after they’ve decided on high-level campaigns and their needs.

As such, consider the core of what you need to study. Can your survey be applied to a macro-application? For example, in the business sector, this can be marketing, branding, advertising, etc.

Next, does your study require a methodical approach? For example, does it need to focus on one period of time among one population? If so, you will need to conduct a cross-sectional survey. 

Or does it require to be conducted over some period of time? This will require implementing a longitudinal study. Once you figure out these components, you should move on to choosing the type of survey research you’re going to conduct. However, you can also decide on this before you choose one of the methodical methods. 

Whichever route you decide to take, you’ll need a strong online survey provider, as this does, after all, involve surveys. The correct online survey platform will set your research up for success.  

Frequently asked questions

Why is it important to understand the types of survey research.

The type of survey research informs the kind of study you’ll be conducting. It becomes the backbone of your campaign and all its implications. Basically, the types of survey research host their designated research methods, which house the surveys. Therefore, the types of survey research you decide on are at the highest level of the research process and act as your starting point.

What is exploratory research?

Exploratory research is the most preliminary form of research, establishing the foundation of a research process. focuses on unearthing ideas and insights rather than gathering statistics. It’s not a conclusive form of research-- rather, it is conducted to bolster understanding of a specific phenomenon. It is typically the first form of research, setting the foundation for a research campaign.

What is descriptive research?

Descriptive research focuses on describing a topic of study like a population, an occurrence or a phenomenon. It is performed early on in the overall research process, as it paints an overall picture of a topic, while extracting the key details that you wouldn’t find with exploratory research alone.

What is a cross-sectional survey?

A cross-sectional survey is a survey used to gather research about a particular population at a specific point in time. It is considered to be the snapshot of a studied population.

What is causal research?

Causal research is typically performed in the latter stages of the entire research process, following correlational or descriptive research. It is conducted to find the causality between variables. It involves more than merely observing, as it relies on experiments and the manipulation of variables

How can you decide which types of survey research to conduct?

Take a look at the core of what you need to study. Are you trying to focus on one period of time among a population? Does your survey research need to be conducted over a period of time? Questions like these will lead you to the right research type.

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Chapter 9: Survey Research

Overview of Survey Research

Learning Objectives

• Define what survey research is, including its two important characteristics.
• Describe several different ways that survey research can be used and give some examples.

What Is Survey Research?

Survey research  is a quantitative and qualitative method with two important characteristics. First, the variables of interest are measured using self-reports. In essence, survey researchers ask their participants (who are often called respondents  in survey research) to report directly on their own thoughts, feelings, and behaviours. Second, considerable attention is paid to the issue of sampling. In particular, survey researchers have a strong preference for large random samples because they provide the most accurate estimates of what is true in the population. In fact, survey research may be the only approach in psychology in which random sampling is routinely used. Beyond these two characteristics, almost anything goes in survey research. Surveys can be long or short. They can be conducted in person, by telephone, through the mail, or over the Internet. They can be about voting intentions, consumer preferences, social attitudes, health, or anything else that it is possible to ask people about and receive meaningful answers.  Although survey data are often analyzed using statistics, there are many questions that lend themselves to more qualitative analysis.

Most survey research is nonexperimental. It is used to describe single variables (e.g., the percentage of voters who prefer one presidential candidate or another, the prevalence of schizophrenia in the general population) and also to assess statistical relationships between variables (e.g., the relationship between income and health). But surveys can also be experimental. The study by Lerner and her colleagues is a good example. Their use of self-report measures and a large national sample identifies their work as survey research. But their manipulation of an independent variable (anger vs. fear) to assess its effect on a dependent variable (risk judgments) also identifies their work as experimental.

History and Uses of Survey Research

Survey research may have its roots in English and American “social surveys” conducted around the turn of the 20th century by researchers and reformers who wanted to document the extent of social problems such as poverty (Converse, 1987) [1] . By the 1930s, the US government was conducting surveys to document economic and social conditions in the country. The need to draw conclusions about the entire population helped spur advances in sampling procedures. At about the same time, several researchers who had already made a name for themselves in market research, studying consumer preferences for American businesses, turned their attention to election polling. A watershed event was the presidential election of 1936 between Alf Landon and Franklin Roosevelt. A magazine called  Literary Digest  conducted a survey by sending ballots (which were also subscription requests) to millions of Americans. Based on this “straw poll,” the editors predicted that Landon would win in a landslide. At the same time, the new pollsters were using scientific methods with much smaller samples to predict just the opposite—that Roosevelt would win in a landslide. In fact, one of them, George Gallup, publicly criticized the methods of Literary Digest  before the election and all but guaranteed that his prediction would be correct. And of course it was. (We will consider the reasons that Gallup was right later in this chapter.) Interest in surveying around election times has led to several long-term projects, notably the Canadian Election Studies which has measured opinions of Canadian voters around federal elections since 1965.  Anyone can access the data and read about the results of the experiments in these studies.

From market research and election polling, survey research made its way into several academic fields, including political science, sociology, and public health—where it continues to be one of the primary approaches to collecting new data. Beginning in the 1930s, psychologists made important advances in questionnaire design, including techniques that are still used today, such as the Likert scale. (See “What Is a Likert Scale?” in  Section 9.2 “Constructing Survey Questionnaires” .) Survey research has a strong historical association with the social psychological study of attitudes, stereotypes, and prejudice. Early attitude researchers were also among the first psychologists to seek larger and more diverse samples than the convenience samples of university students that were routinely used in psychology (and still are).

Survey research continues to be important in psychology today. For example, survey data have been instrumental in estimating the prevalence of various mental disorders and identifying statistical relationships among those disorders and with various other factors. The National Comorbidity Survey is a large-scale mental health survey conducted in the United States . In just one part of this survey, nearly 10,000 adults were given a structured mental health interview in their homes in 2002 and 2003.  Table 9.1  presents results on the lifetime prevalence of some anxiety, mood, and substance use disorders. (Lifetime prevalence is the percentage of the population that develops the problem sometime in their lifetime.) Obviously, this kind of information can be of great use both to basic researchers seeking to understand the causes and correlates of mental disorders as well as to clinicians and policymakers who need to understand exactly how common these disorders are.

And as the opening example makes clear, survey research can even be used to conduct experiments to test specific hypotheses about causal relationships between variables. Such studies, when conducted on large and diverse samples, can be a useful supplement to laboratory studies conducted on university students. Although this approach is not a typical use of survey research, it certainly illustrates the flexibility of this method.

Key Takeaways

• Survey research is a quantitative approach that features the use of self-report measures on carefully selected samples. It is a flexible approach that can be used to study a wide variety of basic and applied research questions.
• Survey research has its roots in applied social research, market research, and election polling. It has since become an important approach in many academic disciplines, including political science, sociology, public health, and, of course, psychology.

Discussion: Think of a question that each of the following professionals might try to answer using survey research.

• a social psychologist
• an educational researcher
• a market researcher who works for a supermarket chain
• the mayor of a large city
• the head of a university police force
• Converse, J. M. (1987). Survey research in the United States: Roots and emergence, 1890–1960 . Berkeley, CA: University of California Press. ↵
• The lifetime prevalence of a disorder is the percentage of people in the population that develop that disorder at any time in their lives. ↵

A quantitative approach in which variables are measured using self-reports from a sample of the population.

Participants of a survey.

Research Methods in Psychology - 2nd Canadian Edition Copyright © 2015 by Paul C. Price, Rajiv Jhangiani, & I-Chant A. Chiang is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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9 Survey research

Survey research is a research method involving the use of standardised questionnaires or interviews to collect data about people and their preferences, thoughts, and behaviours in a systematic manner. Although census surveys were conducted as early as Ancient Egypt, survey as a formal research method was pioneered in the 1930–40s by sociologist Paul Lazarsfeld to examine the effects of the radio on political opinion formation of the United States. This method has since become a very popular method for quantitative research in the social sciences.

The survey method can be used for descriptive, exploratory, or explanatory research. This method is best suited for studies that have individual people as the unit of analysis. Although other units of analysis, such as groups, organisations or dyads—pairs of organisations, such as buyers and sellers—are also studied using surveys, such studies often use a specific person from each unit as a ‘key informant’ or a ‘proxy’ for that unit. Consequently, such surveys may be subject to respondent bias if the chosen informant does not have adequate knowledge or has a biased opinion about the phenomenon of interest. For instance, Chief Executive Officers may not adequately know employees’ perceptions or teamwork in their own companies, and may therefore be the wrong informant for studies of team dynamics or employee self-esteem.

Survey research has several inherent strengths compared to other research methods. First, surveys are an excellent vehicle for measuring a wide variety of unobservable data, such as people’s preferences (e.g., political orientation), traits (e.g., self-esteem), attitudes (e.g., toward immigrants), beliefs (e.g., about a new law), behaviours (e.g., smoking or drinking habits), or factual information (e.g., income). Second, survey research is also ideally suited for remotely collecting data about a population that is too large to observe directly. A large area—such as an entire country—can be covered by postal, email, or telephone surveys using meticulous sampling to ensure that the population is adequately represented in a small sample. Third, due to their unobtrusive nature and the ability to respond at one’s convenience, questionnaire surveys are preferred by some respondents. Fourth, interviews may be the only way of reaching certain population groups such as the homeless or illegal immigrants for which there is no sampling frame available. Fifth, large sample surveys may allow detection of small effects even while analysing multiple variables, and depending on the survey design, may also allow comparative analysis of population subgroups (i.e., within-group and between-group analysis). Sixth, survey research is more economical in terms of researcher time, effort and cost than other methods such as experimental research and case research. At the same time, survey research also has some unique disadvantages. It is subject to a large number of biases such as non-response bias, sampling bias, social desirability bias, and recall bias, as discussed at the end of this chapter.

Depending on how the data is collected, survey research can be divided into two broad categories: questionnaire surveys (which may be postal, group-administered, or online surveys), and interview surveys (which may be personal, telephone, or focus group interviews). Questionnaires are instruments that are completed in writing by respondents, while interviews are completed by the interviewer based on verbal responses provided by respondents. As discussed below, each type has its own strengths and weaknesses in terms of their costs, coverage of the target population, and researcher’s flexibility in asking questions.

Questionnaire surveys

Invented by Sir Francis Galton, a questionnaire is a research instrument consisting of a set of questions (items) intended to capture responses from respondents in a standardised manner. Questions may be unstructured or structured. Unstructured questions ask respondents to provide a response in their own words, while structured questions ask respondents to select an answer from a given set of choices. Subjects’ responses to individual questions (items) on a structured questionnaire may be aggregated into a composite scale or index for statistical analysis. Questions should be designed in such a way that respondents are able to read, understand, and respond to them in a meaningful way, and hence the survey method may not be appropriate or practical for certain demographic groups such as children or the illiterate.

Most questionnaire surveys tend to be self-administered postal surveys , where the same questionnaire is posted to a large number of people, and willing respondents can complete the survey at their convenience and return it in prepaid envelopes. Postal surveys are advantageous in that they are unobtrusive and inexpensive to administer, since bulk postage is cheap in most countries. However, response rates from postal surveys tend to be quite low since most people ignore survey requests. There may also be long delays (several months) in respondents’ completing and returning the survey, or they may even simply lose it. Hence, the researcher must continuously monitor responses as they are being returned, track and send non-respondents repeated reminders (two or three reminders at intervals of one to one and a half months is ideal). Questionnaire surveys are also not well-suited for issues that require clarification on the part of the respondent or those that require detailed written responses. Longitudinal designs can be used to survey the same set of respondents at different times, but response rates tend to fall precipitously from one survey to the next.

A second type of survey is a group-administered questionnaire . A sample of respondents is brought together at a common place and time, and each respondent is asked to complete the survey questionnaire while in that room. Respondents enter their responses independently without interacting with one another. This format is convenient for the researcher, and a high response rate is assured. If respondents do not understand any specific question, they can ask for clarification. In many organisations, it is relatively easy to assemble a group of employees in a conference room or lunch room, especially if the survey is approved by corporate executives.

A more recent type of questionnaire survey is an online or web survey. These surveys are administered over the Internet using interactive forms. Respondents may receive an email request for participation in the survey with a link to a website where the survey may be completed. Alternatively, the survey may be embedded into an email, and can be completed and returned via email. These surveys are very inexpensive to administer, results are instantly recorded in an online database, and the survey can be easily modified if needed. However, if the survey website is not password-protected or designed to prevent multiple submissions, the responses can be easily compromised. Furthermore, sampling bias may be a significant issue since the survey cannot reach people who do not have computer or Internet access, such as many of the poor, senior, and minority groups, and the respondent sample is skewed toward a younger demographic who are online much of the time and have the time and ability to complete such surveys. Computing the response rate may be problematic if the survey link is posted on LISTSERVs or bulletin boards instead of being emailed directly to targeted respondents. For these reasons, many researchers prefer dual-media surveys (e.g., postal survey and online survey), allowing respondents to select their preferred method of response.

Constructing a survey questionnaire is an art. Numerous decisions must be made about the content of questions, their wording, format, and sequencing, all of which can have important consequences for the survey responses.

Response formats. Survey questions may be structured or unstructured. Responses to structured questions are captured using one of the following response formats:

Dichotomous response , where respondents are asked to select one of two possible choices, such as true/false, yes/no, or agree/disagree. An example of such a question is: Do you think that the death penalty is justified under some circumstances? (circle one): yes / no.

Nominal response , where respondents are presented with more than two unordered options, such as: What is your industry of employment?: manufacturing / consumer services / retail / education / healthcare / tourism and hospitality / other.

Ordinal response , where respondents have more than two ordered options, such as: What is your highest level of education?: high school / bachelor’s degree / postgraduate degree.

Interval-level response , where respondents are presented with a 5-point or 7-point Likert scale, semantic differential scale, or Guttman scale. Each of these scale types were discussed in a previous chapter.

Continuous response , where respondents enter a continuous (ratio-scaled) value with a meaningful zero point, such as their age or tenure in a firm. These responses generally tend to be of the fill-in-the blanks type.

Question content and wording. Responses obtained in survey research are very sensitive to the types of questions asked. Poorly framed or ambiguous questions will likely result in meaningless responses with very little value. Dillman (1978) [1] recommends several rules for creating good survey questions. Every single question in a survey should be carefully scrutinised for the following issues:

Is the question clear and understandable ?: Survey questions should be stated in very simple language, preferably in active voice, and without complicated words or jargon that may not be understood by a typical respondent. All questions in the questionnaire should be worded in a similar manner to make it easy for respondents to read and understand them. The only exception is if your survey is targeted at a specialised group of respondents, such as doctors, lawyers and researchers, who use such jargon in their everyday environment. Is the question worded in a negative manner ?: Negatively worded questions such as ‘Should your local government not raise taxes?’ tend to confuse many respondents and lead to inaccurate responses. Double-negatives should be avoided when designing survey questions.

Is the question ambiguous ?: Survey questions should not use words or expressions that may be interpreted differently by different respondents (e.g., words like ‘any’ or ‘just’). For instance, if you ask a respondent, ‘What is your annual income?’, it is unclear whether you are referring to salary/wages, or also dividend, rental, and other income, whether you are referring to personal income, family income (including spouse’s wages), or personal and business income. Different interpretation by different respondents will lead to incomparable responses that cannot be interpreted correctly.

Does the question have biased or value-laden words ?: Bias refers to any property of a question that encourages subjects to answer in a certain way. Kenneth Rasinky (1989) [2] examined several studies on people’s attitude toward government spending, and observed that respondents tend to indicate stronger support for ‘assistance to the poor’ and less for ‘welfare’, even though both terms had the same meaning. In this study, more support was also observed for ‘halting rising crime rate’ and less for ‘law enforcement’, more for ‘solving problems of big cities’ and less for ‘assistance to big cities’, and more for ‘dealing with drug addiction’ and less for ‘drug rehabilitation’. A biased language or tone tends to skew observed responses. It is often difficult to anticipate in advance the biasing wording, but to the greatest extent possible, survey questions should be carefully scrutinised to avoid biased language.

Is the question double-barrelled ?: Double-barrelled questions are those that can have multiple answers. For example, ‘Are you satisfied with the hardware and software provided for your work?’. In this example, how should a respondent answer if they are satisfied with the hardware, but not with the software, or vice versa? It is always advisable to separate double-barrelled questions into separate questions: ‘Are you satisfied with the hardware provided for your work?’, and ’Are you satisfied with the software provided for your work?’. Another example: ‘Does your family favour public television?’. Some people may favour public TV for themselves, but favour certain cable TV programs such as Sesame Street for their children.

Is the question too general ?: Sometimes, questions that are too general may not accurately convey respondents’ perceptions. If you asked someone how they liked a certain book and provided a response scale ranging from ‘not at all’ to ‘extremely well’, if that person selected ‘extremely well’, what do they mean? Instead, ask more specific behavioural questions, such as, ‘Will you recommend this book to others, or do you plan to read other books by the same author?’. Likewise, instead of asking, ‘How big is your firm?’ (which may be interpreted differently by respondents), ask, ‘How many people work for your firm?’, and/or ‘What is the annual revenue of your firm?’, which are both measures of firm size.

Is the question too detailed ?: Avoid unnecessarily detailed questions that serve no specific research purpose. For instance, do you need the age of each child in a household, or is just the number of children in the household acceptable? However, if unsure, it is better to err on the side of details than generality.

Is the question presumptuous ?: If you ask, ‘What do you see as the benefits of a tax cut?’, you are presuming that the respondent sees the tax cut as beneficial. Many people may not view tax cuts as being beneficial, because tax cuts generally lead to lesser funding for public schools, larger class sizes, and fewer public services such as police, ambulance, and fire services. Avoid questions with built-in presumptions.

Is the question imaginary ?: A popular question in many television game shows is, ‘If you win a million dollars on this show, how will you spend it?’. Most respondents have never been faced with such an amount of money before and have never thought about it—they may not even know that after taxes, they will get only about $640,000 or so in the United States, and in many cases, that amount is spread over a 20-year period—and so their answers tend to be quite random, such as take a tour around the world, buy a restaurant or bar, spend on education, save for retirement, help parents or children, or have a lavish wedding. Imaginary questions have imaginary answers, which cannot be used for making scientific inferences.

Do respondents have the information needed to correctly answer the question ?: Oftentimes, we assume that subjects have the necessary information to answer a question, when in reality, they do not. Even if a response is obtained, these responses tend to be inaccurate given the subjects’ lack of knowledge about the question being asked. For instance, we should not ask the CEO of a company about day-to-day operational details that they may not be aware of, or ask teachers about how much their students are learning, or ask high-schoolers, ‘Do you think the US Government acted appropriately in the Bay of Pigs crisis?’.

Question sequencing. In general, questions should flow logically from one to the next. To achieve the best response rates, questions should flow from the least sensitive to the most sensitive, from the factual and behavioural to the attitudinal, and from the more general to the more specific. Some general rules for question sequencing:

Start with easy non-threatening questions that can be easily recalled. Good options are demographics (age, gender, education level) for individual-level surveys and firmographics (employee count, annual revenues, industry) for firm-level surveys.

Never start with an open ended question.

If following a historical sequence of events, follow a chronological order from earliest to latest.

Ask about one topic at a time. When switching topics, use a transition, such as, ‘The next section examines your opinions about…’

Use filter or contingency questions as needed, such as, ‘If you answered “yes” to question 5, please proceed to Section 2. If you answered “no” go to Section 3′.

Other golden rules . Do unto your respondents what you would have them do unto you. Be attentive and appreciative of respondents’ time, attention, trust, and confidentiality of personal information. Always practice the following strategies for all survey research:

People’s time is valuable. Be respectful of their time. Keep your survey as short as possible and limit it to what is absolutely necessary. Respondents do not like spending more than 10-15 minutes on any survey, no matter how important it is. Longer surveys tend to dramatically lower response rates.

Always assure respondents about the confidentiality of their responses, and how you will use their data (e.g., for academic research) and how the results will be reported (usually, in the aggregate).

For organisational surveys, assure respondents that you will send them a copy of the final results, and make sure that you follow up with your promise.

Thank your respondents for their participation in your study.

Finally, always pretest your questionnaire, at least using a convenience sample, before administering it to respondents in a field setting. Such pretesting may uncover ambiguity, lack of clarity, or biases in question wording, which should be eliminated before administering to the intended sample.

Interview survey

Interviews are a more personalised data collection method than questionnaires, and are conducted by trained interviewers using the same research protocol as questionnaire surveys (i.e., a standardised set of questions). However, unlike a questionnaire, the interview script may contain special instructions for the interviewer that are not seen by respondents, and may include space for the interviewer to record personal observations and comments. In addition, unlike postal surveys, the interviewer has the opportunity to clarify any issues raised by the respondent or ask probing or follow-up questions. However, interviews are time-consuming and resource-intensive. Interviewers need special interviewing skills as they are considered to be part of the measurement instrument, and must proactively strive not to artificially bias the observed responses.

The most typical form of interview is a personal or face-to-face interview , where the interviewer works directly with the respondent to ask questions and record their responses. Personal interviews may be conducted at the respondent’s home or office location. This approach may even be favoured by some respondents, while others may feel uncomfortable allowing a stranger into their homes. However, skilled interviewers can persuade respondents to co-operate, dramatically improving response rates.

A variation of the personal interview is a group interview, also called a focus group . In this technique, a small group of respondents (usually 6–10 respondents) are interviewed together in a common location. The interviewer is essentially a facilitator whose job is to lead the discussion, and ensure that every person has an opportunity to respond. Focus groups allow deeper examination of complex issues than other forms of survey research, because when people hear others talk, it often triggers responses or ideas that they did not think about before. However, focus group discussion may be dominated by a dominant personality, and some individuals may be reluctant to voice their opinions in front of their peers or superiors, especially while dealing with a sensitive issue such as employee underperformance or office politics. Because of their small sample size, focus groups are usually used for exploratory research rather than descriptive or explanatory research.

A third type of interview survey is a telephone interview . In this technique, interviewers contact potential respondents over the phone, typically based on a random selection of people from a telephone directory, to ask a standard set of survey questions. A more recent and technologically advanced approach is computer-assisted telephone interviewing (CATI). This is increasing being used by academic, government, and commercial survey researchers. Here the interviewer is a telephone operator who is guided through the interview process by a computer program displaying instructions and questions to be asked. The system also selects respondents randomly using a random digit dialling technique, and records responses using voice capture technology. Once respondents are on the phone, higher response rates can be obtained. This technique is not ideal for rural areas where telephone density is low, and also cannot be used for communicating non-audio information such as graphics or product demonstrations.

Role of interviewer. The interviewer has a complex and multi-faceted role in the interview process, which includes the following tasks:

Prepare for the interview: Since the interviewer is in the forefront of the data collection effort, the quality of data collected depends heavily on how well the interviewer is trained to do the job. The interviewer must be trained in the interview process and the survey method, and also be familiar with the purpose of the study, how responses will be stored and used, and sources of interviewer bias. They should also rehearse and time the interview prior to the formal study.

Locate and enlist the co-operation of respondents: Particularly in personal, in-home surveys, the interviewer must locate specific addresses, and work around respondents’ schedules at sometimes undesirable times such as during weekends. They should also be like a salesperson, selling the idea of participating in the study.

Motivate respondents: Respondents often feed off the motivation of the interviewer. If the interviewer is disinterested or inattentive, respondents will not be motivated to provide useful or informative responses either. The interviewer must demonstrate enthusiasm about the study, communicate the importance of the research to respondents, and be attentive to respondents’ needs throughout the interview.

Clarify any confusion or concerns: Interviewers must be able to think on their feet and address unanticipated concerns or objections raised by respondents to the respondents’ satisfaction. Additionally, they should ask probing questions as necessary even if such questions are not in the script.

Observe quality of response: The interviewer is in the best position to judge the quality of information collected, and may supplement responses obtained using personal observations of gestures or body language as appropriate.

Conducting the interview. Before the interview, the interviewer should prepare a kit to carry to the interview session, consisting of a cover letter from the principal investigator or sponsor, adequate copies of the survey instrument, photo identification, and a telephone number for respondents to call to verify the interviewer’s authenticity. The interviewer should also try to call respondents ahead of time to set up an appointment if possible. To start the interview, they should speak in an imperative and confident tone, such as, ‘I’d like to take a few minutes of your time to interview you for a very important study’, instead of, ‘May I come in to do an interview?’. They should introduce themself, present personal credentials, explain the purpose of the study in one to two sentences, and assure respondents that their participation is voluntary, and their comments are confidential, all in less than a minute. No big words or jargon should be used, and no details should be provided unless specifically requested. If the interviewer wishes to record the interview, they should ask for respondents’ explicit permission before doing so. Even if the interview is recorded, the interviewer must take notes on key issues, probes, or verbatim phrases

During the interview, the interviewer should follow the questionnaire script and ask questions exactly as written, and not change the words to make the question sound friendlier. They should also not change the order of questions or skip any question that may have been answered earlier. Any issues with the questions should be discussed during rehearsal prior to the actual interview sessions. The interviewer should not finish the respondent’s sentences. If the respondent gives a brief cursory answer, the interviewer should probe the respondent to elicit a more thoughtful, thorough response. Some useful probing techniques are:

The silent probe: Just pausing and waiting without going into the next question may suggest to respondents that the interviewer is waiting for more detailed response.

Overt encouragement: An occasional ‘uh-huh’ or ‘okay’ may encourage the respondent to go into greater details. However, the interviewer must not express approval or disapproval of what the respondent says.

Ask for elaboration: Such as, ‘Can you elaborate on that?’ or ‘A minute ago, you were talking about an experience you had in high school. Can you tell me more about that?’.

Reflection: The interviewer can try the psychotherapist’s trick of repeating what the respondent said. For instance, ‘What I’m hearing is that you found that experience very traumatic’ and then pause and wait for the respondent to elaborate.

After the interview is completed, the interviewer should thank respondents for their time, tell them when to expect the results, and not leave hastily. Immediately after leaving, they should write down any notes or key observations that may help interpret the respondent’s comments better.

Biases in survey research

Despite all of its strengths and advantages, survey research is often tainted with systematic biases that may invalidate some of the inferences derived from such surveys. Five such biases are the non-response bias, sampling bias, social desirability bias, recall bias, and common method bias.

Non-response bias. Survey research is generally notorious for its low response rates. A response rate of 15-20 per cent is typical in a postal survey, even after two or three reminders. If the majority of the targeted respondents fail to respond to a survey, this may indicate a systematic reason for the low response rate, which may in turn raise questions about the validity of the study’s results. For instance, dissatisfied customers tend to be more vocal about their experience than satisfied customers, and are therefore more likely to respond to questionnaire surveys or interview requests than satisfied customers. Hence, any respondent sample is likely to have a higher proportion of dissatisfied customers than the underlying population from which it is drawn. In this instance, not only will the results lack generalisability, but the observed outcomes may also be an artefact of the biased sample. Several strategies may be employed to improve response rates:

Advance notification: Sending a short letter to the targeted respondents soliciting their participation in an upcoming survey can prepare them in advance and improve their propensity to respond. The letter should state the purpose and importance of the study, mode of data collection (e.g., via a phone call, a survey form in the mail, etc.), and appreciation for their co-operation. A variation of this technique may be to ask the respondent to return a prepaid postcard indicating whether or not they are willing to participate in the study.

Relevance of content: People are more likely to respond to surveys examining issues of relevance or importance to them.

Respondent-friendly questionnaire: Shorter survey questionnaires tend to elicit higher response rates than longer questionnaires. Furthermore, questions that are clear, non-offensive, and easy to respond tend to attract higher response rates.

Endorsement: For organisational surveys, it helps to gain endorsement from a senior executive attesting to the importance of the study to the organisation. Such endorsement can be in the form of a cover letter or a letter of introduction, which can improve the researcher’s credibility in the eyes of the respondents.

Follow-up requests: Multiple follow-up requests may coax some non-respondents to respond, even if their responses are late.

Interviewer training: Response rates for interviews can be improved with skilled interviewers trained in how to request interviews, use computerised dialling techniques to identify potential respondents, and schedule call-backs for respondents who could not be reached.

Incentives : Incentives in the form of cash or gift cards, giveaways such as pens or stress balls, entry into a lottery, draw or contest, discount coupons, promise of contribution to charity, and so forth may increase response rates.

Non-monetary incentives: Businesses, in particular, are more prone to respond to non-monetary incentives than financial incentives. An example of such a non-monetary incentive is a benchmarking report comparing the business’s individual response against the aggregate of all responses to a survey.

Confidentiality and privacy: Finally, assurances that respondents’ private data or responses will not fall into the hands of any third party may help improve response rates

Sampling bias. Telephone surveys conducted by calling a random sample of publicly available telephone numbers will systematically exclude people with unlisted telephone numbers, mobile phone numbers, and people who are unable to answer the phone when the survey is being conducted—for instance, if they are at work—and will include a disproportionate number of respondents who have landline telephone services with listed phone numbers and people who are home during the day, such as the unemployed, the disabled, and the elderly. Likewise, online surveys tend to include a disproportionate number of students and younger people who are constantly on the Internet, and systematically exclude people with limited or no access to computers or the Internet, such as the poor and the elderly. Similarly, questionnaire surveys tend to exclude children and the illiterate, who are unable to read, understand, or meaningfully respond to the questionnaire. A different kind of sampling bias relates to sampling the wrong population, such as asking teachers (or parents) about their students’ (or children’s) academic learning, or asking CEOs about operational details in their company. Such biases make the respondent sample unrepresentative of the intended population and hurt generalisability claims about inferences drawn from the biased sample.

Social desirability bias . Many respondents tend to avoid negative opinions or embarrassing comments about themselves, their employers, family, or friends. With negative questions such as, ‘Do you think that your project team is dysfunctional?’, ‘Is there a lot of office politics in your workplace?’, ‘Or have you ever illegally downloaded music files from the Internet?’, the researcher may not get truthful responses. This tendency among respondents to ‘spin the truth’ in order to portray themselves in a socially desirable manner is called the ‘social desirability bias’, which hurts the validity of responses obtained from survey research. There is practically no way of overcoming the social desirability bias in a questionnaire survey, but in an interview setting, an astute interviewer may be able to spot inconsistent answers and ask probing questions or use personal observations to supplement respondents’ comments.

Recall bias. Responses to survey questions often depend on subjects’ motivation, memory, and ability to respond. Particularly when dealing with events that happened in the distant past, respondents may not adequately remember their own motivations or behaviours, or perhaps their memory of such events may have evolved with time and no longer be retrievable. For instance, if a respondent is asked to describe his/her utilisation of computer technology one year ago, or even memorable childhood events like birthdays, their response may not be accurate due to difficulties with recall. One possible way of overcoming the recall bias is by anchoring the respondent’s memory in specific events as they happened, rather than asking them to recall their perceptions and motivations from memory.

Common method bias. Common method bias refers to the amount of spurious covariance shared between independent and dependent variables that are measured at the same point in time, such as in a cross-sectional survey, using the same instrument, such as a questionnaire. In such cases, the phenomenon under investigation may not be adequately separated from measurement artefacts. Standard statistical tests are available to test for common method bias, such as Harmon’s single-factor test (Podsakoff, MacKenzie, Lee & Podsakoff, 2003), [3] Lindell and Whitney’s (2001) [4] market variable technique, and so forth. This bias can potentially be avoided if the independent and dependent variables are measured at different points in time using a longitudinal survey design, or if these variables are measured using different methods, such as computerised recording of dependent variable versus questionnaire-based self-rating of independent variables.

• Dillman, D. (1978). Mail and telephone surveys: The total design method . New York: Wiley. ↵
• Rasikski, K. (1989). The effect of question wording on public support for government spending. Public Opinion Quarterly , 53(3), 388–394. ↵
• Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology , 88(5), 879–903. http://dx.doi.org/10.1037/0021-9010.88.5.879. ↵
• Lindell, M. K., & Whitney, D. J. (2001). Accounting for common method variance in cross-sectional research designs. Journal of Applied Psychology , 86(1), 114–121. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Survey Research — Types, Methods and Example Questions

Survey research The world of research is vast and complex, but with the right tools and understanding, it's an open field of discovery. Welcome to a journey into the heart of survey research. What is survey research? Survey research is the lens through which we view the opinions, behaviors, and experiences of a population. Think of it as the research world's detective, cleverly sleuthing out the truths hidden beneath layers of human complexity. Why is survey research important? Survey research is a Swiss Army Knife in a researcher's toolbox. It’s adaptable, reliable, and incredibly versatile, but its real power? It gives voice to the silent majority. Whether it's understanding customer preferences or assessing the impact of a social policy, survey research is the bridge between unanswered questions and insightful data. Let's embark on this exploration, armed with the spirit of openness, a sprinkle of curiosity, and the thirst for making knowledge accessible. As we journey further into the realm of survey research, we'll delve deeper into the diverse types of surveys, innovative data collection methods, and the rewards and challenges that come with them. Types of survey research Survey research is like an artist's palette, offering a variety of types to suit your unique research needs. Each type paints a different picture, giving us fascinating insights into the world around us. Cross-Sectional Surveys: Capture a snapshot of a population at a specific moment in time. They're your trusty Polaroid camera, freezing a moment for analysis and understanding. Longitudinal Surveys: Track changes over time, much like a time-lapse video. They help to identify trends and patterns, offering a dynamic perspective of your subject. Descriptive Surveys: Draw a detailed picture of the current state of affairs. They're your magnifying glass, examining the prevalence of a phenomenon or attitudes within a group. Analytical Surveys: Deep dive into the reasons behind certain outcomes. They're the research world's version of Sherlock Holmes, unraveling the complex web of cause and effect. But, what method should you choose for data collection? The plot thickens, doesn't it? Let's unravel this mystery in our next section. Survey research and data collection methods Data collection in survey research is an art form, and there's no one-size-fits-all method. Think of it as your paintbrush, each stroke represents a different way of capturing data. Online Surveys: In the digital age, online surveys have surged in popularity. They're fast, cost-effective, and can reach a global audience. But like a mysterious online acquaintance, respondents may not always be who they say they are. Mail Surveys: Like a postcard from a distant friend, mail surveys have a certain charm. They're great for reaching respondents without internet access. However, they’re slower and have lower response rates. They’re a test of patience and persistence. Telephone Surveys: With the sound of a ringing phone, the human element enters the picture. Great for reaching a diverse audience, they bring a touch of personal connection. But, remember, not all are fans of unsolicited calls. Face-to-Face Surveys: These are the heart-to-heart conversations of the survey world. While they require more resources, they're the gold standard for in-depth, high-quality data. As we journey further, let’s weigh the pros and cons of survey research. Advantages and disadvantages of survey research Every hero has its strengths and weaknesses, and survey research is no exception. Let's unwrap the gift box of survey research to see what lies inside. Advantages: Versatility: Like a superhero with multiple powers, surveys can be adapted to different topics, audiences, and research needs. Accessibility: With online surveys, geographical boundaries dissolve. We can reach out to the world from our living room. Anonymity: Like a confessional booth, surveys allow respondents to share their views without fear of judgment. Disadvantages: Response Bias: Ever met someone who says what you want to hear? Survey respondents can be like that too. Limited Depth: Like a puddle after a rainstorm, some surveys only skim the surface of complex issues. Nonresponse: Sometimes, potential respondents play hard to get, skewing the data. Survey research may have its challenges, but it also presents opportunities to learn and grow. As we forge ahead on our journey, we dive into the design process of survey research. Limitations of survey research Every research method has its limitations, like bumps on the road to discovery. But don't worry, with the right approach, these challenges become opportunities for growth. Misinterpretation: Sometimes, respondents might misunderstand your questions, like a badly translated novel. To overcome this, keep your questions simple and clear. Social Desirability Bias: People often want to present themselves in the best light. They might answer questions in a way that portrays them positively, even if it's not entirely accurate. Overcome this by ensuring anonymity and emphasizing honesty. Sample Representation: If your survey sample isn't representative of the population you're studying, it can skew your results. Aiming for a diverse sample can mitigate this. Now that we're aware of the limitations let's delve into the world of survey design. {loadmoduleid 430} Survey research design Designing a survey is like crafting a roadmap to discovery. It's an intricate process that involves careful planning, innovative strategies, and a deep understanding of your research goals. Let's get started. Approach and Strategy Your approach and strategy are the compasses guiding your survey research. Clear objectives, defined research questions, and an understanding of your target audience lay the foundation for a successful survey. Panel The panel is the heartbeat of your survey, the respondents who breathe life into your research. Selecting a representative panel ensures your research is accurate and inclusive. 9 Tips on Building the Perfect Survey Research Questionnaire Keep It Simple: Clear and straightforward questions lead to accurate responses. Make It Relevant: Ensure every question ties back to your research objectives. Order Matters: Start with easy questions to build rapport and save sensitive ones for later. Avoid Double-Barreled Questions: Stick to one idea per question. Offer a Balanced Scale: For rating scales, provide an equal number of positive and negative options. Provide a ‘Don't Know’ Option: This prevents guessing and keeps your data accurate. Pretest Your Survey: A pilot run helps you spot any issues before the final launch. Keep It Short: Respect your respondents' time. Make It Engaging: Keep your respondents interested with a mix of question types. Survey research examples and questions Examples serve as a bridge connecting theoretical concepts to real-world scenarios. Let's consider a few practical examples of survey research across various domains. User Experience (UX) Imagine being a UX designer at a budding tech start-up. Your app is gaining traction, but to keep your user base growing and engaged, you must ensure that your app's UX is top-notch. In this case, a well-designed survey could be a beacon, guiding you toward understanding user behavior, preferences, and pain points. Here's an example of how such a survey could look: "On a scale of 1 to 10, how would you rate the ease of navigating our app?" "How often do you encounter difficulties while using our app?" "What features do you use most frequently in our app?" "What improvements would you suggest for our app?" "What features would you like to see in future updates?" This line of questioning, while straightforward, provides invaluable insights. It enables the UX designer to identify strengths to capitalize on and weaknesses to improve, ultimately leading to a product that resonates with users. Psychology and Ethics in survey research The realm of survey research is not just about data and numbers, but it's also about understanding human behavior and treating respondents ethically. Psychology: In-depth understanding of cognitive biases and social dynamics can profoundly influence survey design. Let's take the 'Recency Effect,' a psychological principle stating that people tend to remember recent events more vividly than those in the past. While framing questions about user experiences, this insight could be invaluable. For example, a question like "Can you recall an instance in the past week when our customer service exceeded your expectations?" is likely to fetch more accurate responses than asking about an event several months ago. Ethics: On the other hand, maintaining privacy, confidentiality, and informed consent is more than ethical - it's fundamental to the integrity of the research process. Imagine conducting a sensitive survey about workplace culture. Ensuring respondents that their responses will remain confidential and anonymous can encourage more honest responses. An introductory note stating these assurances, along with a clear outline of the survey's purpose, can help build trust with your respondents. Survey research software In the age of digital information, survey research software has become a trusted ally for researchers. It simplifies complex processes like data collection, analysis, and visualization, democratizing research and making it more accessible to a broad audience. LimeSurvey, our innovative, user-friendly tool, brings this vision to life. It stands at the crossroads of simplicity and power, embodying the essence of accessible survey research. Whether you're a freelancer exploring new market trends, a psychology student curious about human behavior, or an HR officer aiming to improve company culture, LimeSurvey empowers you to conduct efficient, effective research. Its suite of features and intuitive design matches your research pace, allowing your curiosity to take the front seat. For instance, consider you're a researcher studying consumer behavior across different demographics. With LimeSurvey, you can easily design demographic-specific questions, distribute your survey across various channels, collect responses in real-time, and visualize your data through intuitive dashboards. This synergy of tools and functionalities makes LimeSurvey a perfect ally in your quest for knowledge. Conclusion If you've come this far, we can sense your spark of curiosity. Are you eager to take the reins and conduct your own survey research? Are you ready to embrace the simple yet powerful tool that LimeSurvey offers? If so, we can't wait to see where your journey takes you next! In the world of survey research, there's always more to explore, more to learn and more to discover. So, keep your curiosity alive, stay open to new ideas, and remember, your exploration is just beginning! We hope that our exploration has been as enlightening for you as it was exciting for us. Remember, the journey doesn't end here. With the power of knowledge and the right tools in your hands, there's no limit to what you can achieve. So, let your curiosity be your guide and dive into the fascinating world of survey research with LimeSurvey! Try it out for free now! Happy surveying! {loadmoduleid 429}

Table Content

Survey research.

The world of research is vast and complex, but with the right tools and understanding, it's an open field of discovery. Welcome to a journey into the heart of survey research.

What is survey research?

Survey research is the lens through which we view the opinions, behaviors, and experiences of a population. Think of it as the research world's detective, cleverly sleuthing out the truths hidden beneath layers of human complexity.

Why is survey research important?

Survey research is a Swiss Army Knife in a researcher's toolbox. It’s adaptable, reliable, and incredibly versatile, but its real power? It gives voice to the silent majority. Whether it's understanding customer preferences or assessing the impact of a social policy, survey research is the bridge between unanswered questions and insightful data.

Let's embark on this exploration, armed with the spirit of openness, a sprinkle of curiosity, and the thirst for making knowledge accessible. As we journey further into the realm of survey research, we'll delve deeper into the diverse types of surveys, innovative data collection methods, and the rewards and challenges that come with them.

Types of survey research

Survey research is like an artist's palette, offering a variety of types to suit your unique research needs. Each type paints a different picture, giving us fascinating insights into the world around us.

• Cross-Sectional Surveys: Capture a snapshot of a population at a specific moment in time. They're your trusty Polaroid camera, freezing a moment for analysis and understanding.
• Longitudinal Surveys: Track changes over time, much like a time-lapse video. They help to identify trends and patterns, offering a dynamic perspective of your subject.
• Descriptive Surveys: Draw a detailed picture of the current state of affairs. They're your magnifying glass, examining the prevalence of a phenomenon or attitudes within a group.
• Analytical Surveys: Deep dive into the reasons behind certain outcomes. They're the research world's version of Sherlock Holmes, unraveling the complex web of cause and effect.

But, what method should you choose for data collection? The plot thickens, doesn't it? Let's unravel this mystery in our next section.

Survey research and data collection methods

Data collection in survey research is an art form, and there's no one-size-fits-all method. Think of it as your paintbrush, each stroke represents a different way of capturing data.

• Online Surveys: In the digital age, online surveys have surged in popularity. They're fast, cost-effective, and can reach a global audience. But like a mysterious online acquaintance, respondents may not always be who they say they are.
• Mail Surveys: Like a postcard from a distant friend, mail surveys have a certain charm. They're great for reaching respondents without internet access. However, they’re slower and have lower response rates. They’re a test of patience and persistence.
• Telephone Surveys: With the sound of a ringing phone, the human element enters the picture. Great for reaching a diverse audience, they bring a touch of personal connection. But, remember, not all are fans of unsolicited calls.
• Face-to-Face Surveys: These are the heart-to-heart conversations of the survey world. While they require more resources, they're the gold standard for in-depth, high-quality data.

As we journey further, let’s weigh the pros and cons of survey research.

Advantages and disadvantages of survey research

Every hero has its strengths and weaknesses, and survey research is no exception. Let's unwrap the gift box of survey research to see what lies inside.

Advantages:

• Versatility: Like a superhero with multiple powers, surveys can be adapted to different topics, audiences, and research needs.
• Accessibility: With online surveys, geographical boundaries dissolve. We can reach out to the world from our living room.
• Anonymity: Like a confessional booth, surveys allow respondents to share their views without fear of judgment.

Disadvantages:

• Response Bias: Ever met someone who says what you want to hear? Survey respondents can be like that too.
• Limited Depth: Like a puddle after a rainstorm, some surveys only skim the surface of complex issues.
• Nonresponse: Sometimes, potential respondents play hard to get, skewing the data.

Survey research may have its challenges, but it also presents opportunities to learn and grow. As we forge ahead on our journey, we dive into the design process of survey research.

Limitations of survey research

Every research method has its limitations, like bumps on the road to discovery. But don't worry, with the right approach, these challenges become opportunities for growth.

Misinterpretation: Sometimes, respondents might misunderstand your questions, like a badly translated novel. To overcome this, keep your questions simple and clear.

Social Desirability Bias: People often want to present themselves in the best light. They might answer questions in a way that portrays them positively, even if it's not entirely accurate. Overcome this by ensuring anonymity and emphasizing honesty.

Sample Representation: If your survey sample isn't representative of the population you're studying, it can skew your results. Aiming for a diverse sample can mitigate this.

Now that we're aware of the limitations let's delve into the world of survey design.

•   Create surveys in 40+ languages
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•   Ready-to-go survey templates
•   So much more...

Survey research design

Designing a survey is like crafting a roadmap to discovery. It's an intricate process that involves careful planning, innovative strategies, and a deep understanding of your research goals. Let's get started.

Approach and Strategy

Your approach and strategy are the compasses guiding your survey research. Clear objectives, defined research questions, and an understanding of your target audience lay the foundation for a successful survey.

The panel is the heartbeat of your survey, the respondents who breathe life into your research. Selecting a representative panel ensures your research is accurate and inclusive.

9 Tips on Building the Perfect Survey Research Questionnaire

• Keep It Simple: Clear and straightforward questions lead to accurate responses.
• Make It Relevant: Ensure every question ties back to your research objectives.
• Order Matters: Start with easy questions to build rapport and save sensitive ones for later.
• Avoid Double-Barreled Questions: Stick to one idea per question.
• Offer a Balanced Scale: For rating scales, provide an equal number of positive and negative options.
• Provide a ‘Don't Know’ Option: This prevents guessing and keeps your data accurate.
• Pretest Your Survey: A pilot run helps you spot any issues before the final launch.
• Keep It Short: Respect your respondents' time.
• Make It Engaging: Keep your respondents interested with a mix of question types.

Survey research examples and questions

Examples serve as a bridge connecting theoretical concepts to real-world scenarios. Let's consider a few practical examples of survey research across various domains.

User Experience (UX)

Imagine being a UX designer at a budding tech start-up. Your app is gaining traction, but to keep your user base growing and engaged, you must ensure that your app's UX is top-notch. In this case, a well-designed survey could be a beacon, guiding you toward understanding user behavior, preferences, and pain points.

Here's an example of how such a survey could look:

• "On a scale of 1 to 10, how would you rate the ease of navigating our app?"
• "How often do you encounter difficulties while using our app?"
• "What features do you use most frequently in our app?"
• "What improvements would you suggest for our app?"
• "What features would you like to see in future updates?"

This line of questioning, while straightforward, provides invaluable insights. It enables the UX designer to identify strengths to capitalize on and weaknesses to improve, ultimately leading to a product that resonates with users.

Psychology and Ethics in survey research

The realm of survey research is not just about data and numbers, but it's also about understanding human behavior and treating respondents ethically.

Psychology: In-depth understanding of cognitive biases and social dynamics can profoundly influence survey design. Let's take the 'Recency Effect,' a psychological principle stating that people tend to remember recent events more vividly than those in the past. While framing questions about user experiences, this insight could be invaluable.

For example, a question like "Can you recall an instance in the past week when our customer service exceeded your expectations?" is likely to fetch more accurate responses than asking about an event several months ago.

Ethics: On the other hand, maintaining privacy, confidentiality, and informed consent is more than ethical - it's fundamental to the integrity of the research process.

Imagine conducting a sensitive survey about workplace culture. Ensuring respondents that their responses will remain confidential and anonymous can encourage more honest responses. An introductory note stating these assurances, along with a clear outline of the survey's purpose, can help build trust with your respondents.

Survey research software

In the age of digital information, survey research software has become a trusted ally for researchers. It simplifies complex processes like data collection, analysis, and visualization, democratizing research and making it more accessible to a broad audience.

LimeSurvey, our innovative, user-friendly tool, brings this vision to life. It stands at the crossroads of simplicity and power, embodying the essence of accessible survey research.

Whether you're a freelancer exploring new market trends, a psychology student curious about human behavior, or an HR officer aiming to improve company culture, LimeSurvey empowers you to conduct efficient, effective research. Its suite of features and intuitive design matches your research pace, allowing your curiosity to take the front seat.

For instance, consider you're a researcher studying consumer behavior across different demographics. With LimeSurvey, you can easily design demographic-specific questions, distribute your survey across various channels, collect responses in real-time, and visualize your data through intuitive dashboards. This synergy of tools and functionalities makes LimeSurvey a perfect ally in your quest for knowledge.

If you've come this far, we can sense your spark of curiosity. Are you eager to take the reins and conduct your own survey research? Are you ready to embrace the simple yet powerful tool that LimeSurvey offers? If so, we can't wait to see where your journey takes you next!

In the world of survey research, there's always more to explore, more to learn and more to discover. So, keep your curiosity alive, stay open to new ideas, and remember, your exploration is just beginning!

We hope that our exploration has been as enlightening for you as it was exciting for us. Remember, the journey doesn't end here. With the power of knowledge and the right tools in your hands, there's no limit to what you can achieve. So, let your curiosity be your guide and dive into the fascinating world of survey research with LimeSurvey! Try it out for free now!

Happy surveying!

Think one step ahead.

Step into a bright future with our simple online survey tool

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A Comprehensive Guide to Survey Research Methodologies

For decades, researchers and businesses have used survey research to produce statistical data and explore ideas. The survey process is simple, ask questions and analyze the responses to make decisions. Data is what makes the difference between a valid and invalid statement and as the American statistician, W. Edwards Deming said:

“Without data, you’re just another person with an opinion.” - W. Edwards Deming

In this article, we will discuss what survey research is, its brief history, types, common uses, benefits, and the step-by-step process of designing a survey.

What is Survey Research

A survey is a research method that is used to collect data from a group of respondents in order to gain insights and information regarding a particular subject. It’s an excellent method to gather opinions and understand how and why people feel a certain way about different situations and contexts.

Brief History of Survey Research

Survey research may have its roots in the American and English “social surveys” conducted around the turn of the 20th century. The surveys were mainly conducted by researchers and reformers to document the extent of social issues such as poverty. ( 1 ) Despite being a relatively young field to many scientific domains, survey research has experienced three stages of development ( 2 ):

-       First Era (1930-1960)

-       Second Era (1960-1990)

-       Third Era (1990 onwards)

Over the years, survey research adapted to the changing times and technologies. By exploiting the latest technologies, researchers can gain access to the right population from anywhere in the world, analyze the data like never before, and extract useful information.

Survey Research Methods & Types

Survey research can be classified into seven categories based on objective, data sources, methodology, deployment method, and frequency of deployment.

Surveys based on Objective

Exploratory survey research.

Exploratory survey research is aimed at diving deeper into research subjects and finding out more about their context. It’s important for marketing or business strategy and the focus is to discover ideas and insights instead of gathering statistical data.

Generally, exploratory survey research is composed of open-ended questions that allow respondents to express their thoughts and perspectives. The final responses present information from various sources that can lead to fresh initiatives.

Predictive Survey Research

Predictive survey research is also called causal survey research. It’s preplanned, structured, and quantitative in nature. It’s often referred to as conclusive research as it tries to explain the cause-and-effect relationship between different variables. The objective is to understand which variables are causes and which are effects and the nature of the relationship between both variables.

Descriptive Survey Research

Descriptive survey research is largely observational and is ideal for gathering numeric data. Due to its quantitative nature, it’s often compared to exploratory survey research. The difference between the two is that descriptive research is structured and pre-planned.

 The idea behind descriptive research is to describe the mindset and opinion of a particular group of people on a given subject. The questions are every day multiple choices and users must choose from predefined categories. With predefined choices, you don’t get unique insights, rather, statistically inferable data.

Survey Research Types based on Concept Testing

Monadic concept testing.

Monadic testing is a survey research methodology in which the respondents are split into multiple groups and ask each group questions about a separate concept in isolation. Generally, monadic surveys are hyper-focused on a particular concept and shorter in duration. The important thing in monadic surveys is to avoid getting off-topic or exhausting the respondents with too many questions.

Sequential Monadic Concept Testing

Another approach to monadic testing is sequential monadic testing. In sequential monadic surveys, groups of respondents are surveyed in isolation. However, instead of surveying three groups on three different concepts, the researchers survey the same groups of people on three distinct concepts one after another. In a sequential monadic survey, at least two topics are included (in random order), and the same questions are asked for each concept to eliminate bias.

Based on Data Source

Primary data.

Data obtained directly from the source or target population is referred to as primary survey data. When it comes to primary data collection, researchers usually devise a set of questions and invite people with knowledge of the subject to respond. The main sources of primary data are interviews, questionnaires, surveys, and observation methods.

 Compared to secondary data, primary data is gathered from first-hand sources and is more reliable. However, the process of primary data collection is both costly and time-consuming.

Secondary Data

Survey research is generally used to collect first-hand information from a respondent. However, surveys can also be designed to collect and process secondary data. It’s collected from third-party sources or primary sources in the past.

 This type of data is usually generic, readily available, and cheaper than primary data collection. Some common sources of secondary data are books, data collected from older surveys, online data, and data from government archives. Beware that you might compromise the validity of your findings if you end up with irrelevant or inflated data.

Based on Research Method

Quantitative research.

Quantitative research is a popular research methodology that is used to collect numeric data in a systematic investigation. It’s frequently used in research contexts where statistical data is required, such as sciences or social sciences. Quantitative research methods include polls, systematic observations, and face-to-face interviews.

Qualitative Research

Qualitative research is a research methodology where you collect non-numeric data from research participants. In this context, the participants are not restricted to a specific system and provide open-ended information. Some common qualitative research methods include focus groups, one-on-one interviews, observations, and case studies.

Based on Deployment Method

Online surveys.

With technology advancing rapidly, the most popular method of survey research is an online survey. With the internet, you can not only reach a broader audience but also design and customize a survey and deploy it from anywhere. Online surveys have outperformed offline survey methods as they are less expensive and allow researchers to easily collect and analyze data from a large sample.

Paper or Print Surveys

As the name suggests, paper or print surveys use the traditional paper and pencil approach to collect data. Before the invention of computers, paper surveys were the survey method of choice.

Though many would assume that surveys are no longer conducted on paper, it's still a reliable method of collecting information during field research and data collection. However, unlike online surveys, paper surveys are expensive and require extra human resources.

Telephonic Surveys

Telephonic surveys are conducted over telephones where a researcher asks a series of questions to the respondent on the other end. Contacting respondents over a telephone requires less effort, human resources, and is less expensive.

What makes telephonic surveys debatable is that people are often reluctant in giving information over a phone call. Additionally, the success of such surveys depends largely on whether people are willing to invest their time on a phone call answering questions.

One-on-one Surveys

One-on-one surveys also known as face-to-face surveys are interviews where the researcher and respondent. Interacting directly with the respondent introduces the human factor into the survey.

Face-to-face interviews are useful when the researcher wants to discuss something personal with the respondent. The response rates in such surveys are always higher as the interview is being conducted in person. However, these surveys are quite expensive and the success of these depends on the knowledge and experience of the researcher.

Based on Distribution

The easiest and most common way of conducting online surveys is sending out an email. Sending out surveys via emails has a higher response rate as your target audience already knows about your brand and is likely to engage.

Buy Survey Responses

Purchasing survey responses also yields higher responses as the responders signed up for the survey. Businesses often purchase survey samples to conduct extensive research. Here, the target audience is often pre-screened to check if they're qualified to take part in the research.

Embedding Survey on a Website

Embedding surveys on a website is another excellent way to collect information. It allows your website visitors to take part in a survey without ever leaving the website and can be done while a person is entering or exiting the website.

Post the Survey on Social Media

Social media is an excellent medium to reach abroad range of audiences. You can publish your survey as a link on social media and people who are following the brand can take part and answer questions.

Based on Frequency of Deployment

Cross-sectional studies.

Cross-sectional studies are administered to a small sample from a large population within a short period of time. This provides researchers a peek into what the respondents are thinking at a given time. The surveys are usually short, precise, and specific to a particular situation.

Longitudinal Surveys

Longitudinal surveys are an extension of cross-sectional studies where researchers make an observation and collect data over extended periods of time. This type of survey can be further divided into three types:

-       Trend surveys are employed to allow researchers to understand the change in the thought process of the respondents over some time.

-       Panel surveys are administered to the same group of people over multiple years. These are usually expensive and researchers must stick to their panel to gather unbiased opinions.

-       In cohort surveys, researchers identify a specific category of people and regularly survey them. Unlike panel surveys, the same people do not need to take part over the years, but each individual must fall into the researcher’s primary interest category.

Retrospective Survey

Retrospective surveys allow researchers to ask questions to gather data about past events and beliefs of the respondents. Since retrospective surveys also require years of data, they are similar to the longitudinal survey, except retrospective surveys are shorter and less expensive.

Why Should You Conduct Research Surveys?

“In God we trust. All others must bring data” - W. Edwards Deming

 In the information age, survey research is of utmost importance and essential for understanding the opinion of your target population. Whether you’re launching a new product or conducting a social survey, the tool can be used to collect specific information from a defined set of respondents. The data collected via surveys can be further used by organizations to make informed decisions.

Furthermore, compared to other research methods, surveys are relatively inexpensive even if you’re giving out incentives. Compared to the older methods such as telephonic or paper surveys, online surveys have a smaller cost and the number of responses is higher.

 What makes surveys useful is that they describe the characteristics of a large population. With a larger sample size , you can rely on getting more accurate results. However, you also need honest and open answers for accurate results. Since surveys are also anonymous and the responses remain confidential, respondents provide candid and accurate answers.

Common Uses of a Survey

Surveys are widely used in many sectors, but the most common uses of the survey research include:

-       Market research : surveying a potential market to understand customer needs, preferences, and market demand.

-       Customer Satisfaction: finding out your customer’s opinions about your services, products, or companies .

-       Social research: investigating the characteristics and experiences of various social groups.

-       Health research: collecting data about patients’ symptoms and treatments.

-       Politics: evaluating public opinion regarding policies and political parties.

-       Psychology: exploring personality traits, behaviors, and preferences.

6 Steps to Conduct Survey Research

An organization, person, or company conducts a survey when they need the information to make a decision but have insufficient data on hand. Following are six simple steps that can help you design a great survey.

Step 1: Objective of the Survey

The first step in survey research is defining an objective. The objective helps you define your target population and samples. The target population is the specific group of people you want to collect data from and since it’s rarely possible to survey the entire population, we target a specific sample from it. Defining a survey objective also benefits your respondents by helping them understand the reason behind the survey.

Step 2: Number of Questions

The number of questions or the size of the survey depends on the survey objective. However, it’s important to ensure that there are no redundant queries and the questions are in a logical order. Rephrased and repeated questions in a survey are almost as frustrating as in real life. For a higher completion rate, keep the questionnaire small so that the respondents stay engaged to the very end. The ideal length of an interview is less than 15 minutes. ( 2 )

Step 3: Language and Voice of Questions

While designing a survey, you may feel compelled to use fancy language. However, remember that difficult language is associated with higher survey dropout rates. You need to speak to the respondent in a clear, concise, and neutral manner, and ask simple questions. If your survey respondents are bilingual, then adding an option to translate your questions into another language can also prove beneficial.

Step 4: Type of Questions

In a survey, you can include any type of questions and even both closed-ended or open-ended questions. However, opt for the question types that are the easiest to understand for the respondents, and offer the most value. For example, compared to open-ended questions, people prefer to answer close-ended questions such as MCQs (multiple choice questions)and NPS (net promoter score) questions.

Step 5: User Experience

Designing a great survey is about more than just questions. A lot of researchers underestimate the importance of user experience and how it affects their response and completion rates. An inconsistent, difficult-to-navigate survey with technical errors and poor color choice is unappealing for the respondents. Make sure that your survey is easy to navigate for everyone and if you’re using rating scales, they remain consistent throughout the research study.

Additionally, don’t forget to design a good survey experience for both mobile and desktop users. According to Pew Research Center, nearly half of the smartphone users access the internet mainly from their mobile phones and 14 percent of American adults are smartphone-only internet users. ( 3 )

Step 6: Survey Logic

Last but not least, logic is another critical aspect of the survey design. If the survey logic is flawed, respondents may not continue in the right direction. Make sure to test the logic to ensure that selecting one answer leads to the next logical question instead of a series of unrelated queries.

How to Effectively Use Survey Research with Starlight Analytics

Designing and conducting a survey is almost as much science as it is an art. To craft great survey research, you need technical skills, consider the psychological elements, and have a broad understanding of marketing.

The ultimate goal of the survey is to ask the right questions in the right manner to acquire the right results.

Bringing a new product to the market is a long process and requires a lot of research and analysis. In your journey to gather information or ideas for your business, Starlight Analytics can be an excellent guide. Starlight Analytics' product concept testing helps you measure your product's market demand and refine product features and benefits so you can launch with confidence. The process starts with custom research to design the survey according to your needs, execute the survey, and deliver the key insights on time.

• Survey research in the United States: roots and emergence, 1890-1960 https://searchworks.stanford.edu/view/10733873    
• How to create a survey questionnaire that gets great responses https://luc.id/knowledgehub/how-to-create-a-survey-questionnaire-that-gets-great-responses/    
• Internet/broadband fact sheet https://www.pewresearch.org/internet/fact-sheet/internet-broadband/    

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Home Surveys

Types of Survey: What It Is with Examples

Technically, a  survey is a method of gathering and compiling information from a group of people, more often known as the sample, to gain knowledge by organizations, businesses, or institutions. This information or opinion collected from the sample is more often a generalization of what a large population thinks.

Different types of survey helps provide important or critical information in the form of meaningful data, which is further used by businesses or organizations to make informed and sound decisions. The collected data offers good insights only when the administered questionnaire is carefully designed to promote response rates and includes both open-ended questions and closed-ended questions and answers options. There is much variety when it comes to surveys, and we can identify their types based on the frequency of their administration or the way of deployment.

LEARN ABOUT:  Testimonial Questions

Types of Survey

Now that we know what a survey is and why do we need to survey people, let’s explore its types. These can be classified in different ways, as mentioned earlier, depending upon the frequency of administration or deployment and how the distribution/deployment occurs. There are other types of surveys like random sample surveys (to understand public opinion or attitude) and self-selected type of studies.

LEARN ABOUT: Candidate Experience Survey

Types of a survey based on deployment methods:

1. online surveys:.

One of the most popular types is an online survey . With technology advancing many folds with each passing day, an online survey is becoming more popular. This survey consists of  survey questions that can be easily deployed to the respondents online via email, or they can access the survey if they have an internet connection. These surveys are easy to design and simple to deploy. Respondents are given ample time and space to the respondent to answer these surveys, so researchers can expect unbiased responses. They are less expensive, and data can be collected and analyzed quickly.

LEARN ABOUT: Event Surveys

2. Paper surveys:

As the name suggests, this survey uses the traditional paper and pencil approach. Many would believe that paper surveys are a thing of the past. However, they are quite handy when it comes to field research and data collection. These surveys can go where computers, laptops or other handheld devices cannot go.

There is a flip side to it too. This survey type is the most expensive method of data collection. It includes deploying a large number of human resources, along with time and money.

LEARN ABOUT: course evaluation survey examples

3. Telephonic Surveys:

Researchers conduct these over telephones. Respondents need to answer questions related to the research topic by the researcher. These surveys are time-consuming and sometimes non-conclusive. The success of these depends on how many people answer the phone and want to invest their time answering questions over the telephone.

4. One-to-One interviews:

The one-to-one interview helps researchers gather information or data directly from a respondent. It’s a qualitative research method  and depends on the knowledge and experience of a researcher to frame and ask relevant questions one after the other to collect meaningful insights from the  interview . These interviews can last from 30 minutes up to a few hours.

Types of a survey based on the frequency of deployment

1. cross-sectional studies.

These surveys are administered to a small sample from a larger population within a small time frame. This type offers a researcher a quick summary or analysis of what respondents think at that given time. These surveys are short and ready to answer and can measure opinion in one particular situation.

Consider hypothetically, an organization conducts a study related to breast cancer in America, and they choose a sample to obtain cross-sectional data. This data indicated that breast cancer was most prevalent in women of African-American origin. The information is from one point in time. Now, if the researcher wants to dwell more in-depth into the research, he/she can deploy a longitudinal survey.

Learn more: Cross-sectional Study

2. Longitudinal surveys:

Longitudinal surveys are those surveys that help researchers to make an observation and collect data over an extended period. There are three main types of longitudinal studies: trend surveys, panel surveys, and cohort surveys.

Trend surveys are deployed by researchers to understand the shift or transformation in the thought process of respondents over some time. They use these surveys to understand how people’s inclination change with time.

Another longitudinal survey type is  a panel survey . Researchers administer these surveys to the same set or group of people over the years. Panel surveys are expensive in nature, and researchers try to stick to their panel to gather unbiased opinions.

The third type of longitudinal survey is the cohort survey. In this type, categories of people that meet specific similar criteria and characteristics form the target audience. The same people don’t need to create a group. However, people forming a group should have certain similarities.

Learn more: Longitudinal Study

3. Retrospective survey:

A retrospective survey is a type of study in which respondents answer questions to report on events from the past. By deploying this kind of survey, researchers can gather data based on past experiences and beliefs of people. This way, unlike a longitudinal survey, they can save the cost and time required.

Learn more: Cross-sectional vs Longitudinal Study

Random public opinion/attitude type of survey research:

When an agency needs reliable, projectable data about the attitudes and opinions of its citizens or a select group of its citizens, it is essential to conduct a valid, random sample survey. Telephone interview surveys are considerably more common than in-person interviews because they are far less expensive to administer and act as a standard tool for gathering information.

There is a margin of error based on the sample size (generally, a minimum population sample of 200 is the industry standard for reliable data about any population segment). Overall, random sample telephone interview surveys provide reasonably accurate information about the population.

While there is a statistical  margin of error (the sample of 200 provides an error range of +/- 7% with a 95% confidence), this type of survey is the most democratic and reliable process for learning about the opinions of an entire community.

A random sample survey is inappropriate for educating people about an issue or assessing what people will do at some future point (i.e., “Will you vote for this bond issue?”). But, the results provide a reasonably accurate portrait of the person’s opinions in the present moment (i.e., a person’s feelings or attitudes about the issues relating to the need to approve a bond). Questions in the past and present tense provide a reasonable degree of accuracy about a person’s usage and habit patterns.

If you are trying to calculate the ideal margin of error for your research, you can use tools like our margin of error calculator .

LEARN ABOUT: telephone survey

Self-selected type of survey research – Newspapers, mail, Internet, written questionnaires:

When an agency has a political need to create a survey process that allows anyone interested in responding, it can do a self-selected process. A written survey can be distributed in public locations, such as the City Hall or Library, emailed directly, emailed, or published in the city newsletter or the local newspaper.

When reporting data from a self-selected survey, it is essential, to begin with, the understanding and the language, “Of those who chose to respond…..” Most often, those who volunteer to respond to a self-selected survey have a strong opinion (frequently negative) about the issue in question.

A self-selected survey can be an excellent public relations tool and the right way to inform the public. But, it’s crucial to be cautious in drawing any conclusion about what the public, in general, thinks based on the results of a survey when the respondents are volunteers.

Learn more: Research Design

Types of surveys with examples

A researcher must have a proper medium to conduct research and collect meaningful information to make informed decisions. Also, it is essential to have a platform to create and deploy these various types of market research surveys.

LEARN ABOUT: Top 12 Tips to Create A Good Survey

QuestionPro is a platform that helps not only to create but also to deploy different types of surveys. We have 350+ types of survey templates and survey examples, including:

• Customer survey templates: Customers are crucial to success for any business or organization, and so are customer satisfaction surveys. It is essential for organizations or companies to understand their customers and what their needs and preferences are. Use the customer survey template to understand your customers better and work on their feedback to grow and flourish your business.
• Market research & Marketing survey templates : Use marketing survey templates for market research to determine what consumers think about products or services. These are also helpful for a brand to assess whether products are reasonably priced, gather feedback from consumers, measure their level of awareness, and more.
• Community survey templates : Community survey templates can be administered to members of associations or foundations to get feedback regarding the various activities conducted within the association. This helps understand the member’s experiences and collect feedback regarding what kind of programs add value, feedback of previously held events, etc. and more.
• Human Resource survey templates : The human resource survey template can be used by businesses and organizations for employee evaluation, employee satisfaction, employee engagement, and more. Organizations can send these out to employees, and their feedback can be collected and implemented.

LEARN ABOUT:   Workforce Planning Model

• Industrial survey templates : Expertly designed survey templates that are customized for the different industries help to collect in-depth feedback or information from consumers of various industries like event management, hotel industry , fast food industry, transportation, just to name a few. Through these survey templates, the industry player can understand what good they are already doing and what needs more attention from a consumer’s point of view.
• Academic survey templates : Academic survey templates are one of the best ways to understand how students and their parents respond to the efforts taken by your education institution. A online questionnaire designed by industry experts helps to assess the parent/student feedback on a course evaluation, curriculum planning, training sessions, etc.
• Nonprofit survey templates : These Nonprofit survey templates are designed by domain experts to collect targeted information and feedback from various donors, volunteers, stakeholders, and any other participants of a nonprofit’s activities. The questionnaires address various important touchpoints and collect data from event attendees, collect donor survey feedback, or run an internal survey among volunteers.

LEARN ABOUT: best time to send out surveys

One can choose from these existing survey format templates or create a survey of their own, all this just at the click of a button.

Explore: 350+ Free survey templates

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When to Use Surveys in Psychology Research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

 James Lacy, MLS, is a fact-checker and researcher.

Reasons to Use Surveys in Psychology

• How to Use Surveys
• Disadvantages

Types of Psychological Surveys

• Important Considerations

A survey is a data collection tool used to gather information about individuals. Surveys are commonly used in psychology research to collect self-report data from study participants. A survey may focus on factual information about individuals, or it might aim to obtain the opinions of the survey takers.

Psychology surveys involve asking participants a series of questions to learn more about a phenomenon, such as how they think, feel, or behave. Such tools can be helpful for learning about behaviors, conditions, traits, or other topics that interest researchers.

At a Glance

Psychological surveys are a valuable research tool that allow scientists to collect large quantities of data relatively quickly. However, such surveys sometimes have low response rates that can lead to biased results. Learning more about how surveys are used in psychology can give you a better understanding of how this type of research can be used to learn more about the human mind and behavior.

So why do psychologists opt to use surveys so often in psychology research?

Surveys are one of the most commonly used research tools   because they can be utilized to collect data and describe naturally occurring phenomena that exist in the real world.

They offer researchers a way to collect a great deal of information in a relatively quick and easy way. A large number of responses can be obtained quite quickly, which allows scientists to work with a lot of data.

Surveys in psychology are vital because they allow researchers to:

• Understand the experiences, opinions, and behaviors of the participants
• Evaluate respondent attitudes and beliefs
• Look at the risk factors in a sample
• Assess individual differences
• Evaluate the success of interventions or preventative programs

How to Use Surveys in Psychology

A survey can be used to investigate the characteristics, behaviors, or opinions of a group of people. These research tools can be used to ask questions about demographic information about characteristics such as sex, religion, ethnicity, and income.

They can also collect information on experiences, opinions, and even hypothetical scenarios. For example, researchers might present people with a possible scenario and then ask them how they might respond in that situation.

How do researchers go about collecting information using surveys?

How Surveys Are Administered

A survey can be administered in a couple of different ways:

• Structured interview: The researcher asks each participant the questions
• Questionnaire: the participant fills out the survey independently

You have probably taken many different surveys in the past, although the questionnaire method tends to be the most common.  

Surveys are generally standardized to ensure that they have reliability and validity . Standardization is also important so that the results can be generalized to the larger population.

Advantages of Psychological Surveys

One of the big benefits of using surveys in psychological research is that they allow researchers to gather a large quantity of data relatively quickly and cheaply.

A survey can be administered as a structured interview or as a self-report measure, and data can be collected in person, over the phone, or on a computer.

• Data collection : Surveys allow researchers to collect a large amount of data in a relatively short period.
• Cost-effectiveness : Surveys are less expensive than many other data collection techniques.
• Ease of administration : Surveys can be created quickly and administered easily.
• Usefulness : Surveys can be used to collect information on a broad range of things, including personal facts, attitudes, past behaviors, and opinions.

Disadvantages of Using Surveys in Psychology

One potential problem with written surveys is the nonresponse bias.

Experts suggest that return rates of 85% or higher are considered excellent, but anything below 60% might severely impact the sample's representativeness .

• Problems with construction and administration : Poor survey construction and administration can undermine otherwise well-designed studies.
• Inaccuracy : The answer choices provided in a survey may not be an accurate reflection of how the participants actually feel.
• Poor response rates : While random sampling is generally used to select participants, response rates can bias the results of a survey. Strategies to improve response rates sometimes include offering financial incentives, sending personalized invitations, and reminding participants to complete the survey.
• Biased results : The social desirability bias can lead people to respond in a way that makes them look better than they really are. For example, a respondent might report that they engage in more healthy behaviors than they do in real life.

Less expensive

Easy to create and administer

Diverse uses

Subject to nonresponse bias

May be poorly designed

Limited answer choices can influence results

Subject to social desirability bias

Surveys can be implemented in a number of different ways. The chances are good that you have participated in a number of different market research surveys in the past.

Some of the most common ways to administer surveys include:

• Mail : An example might include an alumni survey distributed via direct mail by your alma mater.
• Telephone : An example of a telephone survey would be a market research call about your experiences with a certain consumer product.
• Online : Online surveys might focus on your experience with a particular retailer, product, or website.
• At-home interviews : The U.S. Census is a good example of an at-home interview survey administration.

Important Considerations When Using Psychological Surveys

When researchers are using surveys in psychology research, there are important ethical factors they need to consider while collecting data.

• Obtaining informed consent is vital : Before administering a psychological survey, all participants should be informed about the purpose and potential risks before responding.
• Creating a representative sample : Researchers should ensure that their participant sample is representative of the larger population. This involves including participants who are part of diverse populations.
• Participation must be voluntary : Anyone who responds to a survey must do so of their own free will. They should not feel coerced or bribed into participating. 
• Take steps to reduce bias : Questions should be carefully constructed so they do not affect how the participants respond. Researchers should also be cautious to avoid insensitive or offensive questions.
• Confidentiality : All survey responses should be kept confidential. Researchers often utilize special software that ensures privacy, protects data, and avoids using identifiable information.

Psychological surveys can be powerful, convenient, and informative research tools. Researchers often utilize surveys in psychology to collect data about how participants think, feel, or behave. While useful, it is important to construct these surveys carefully to avoid asking leading questions and reduce bias.

National Science Foundation. Directorate for Education and Human Resources Division of Research, Evaluation and Communication. The 2002 User-Friendly Handbook for Project Evaluation. Section III. An Overview of Quantitative and Qualitative Data Collection Methods. 5. Data collection methods: Some tips and comparisons. Arlington, Va.: The National Science Foundation, 2002.

Jones TL, Baxter MA, Khanduja V. A quick guide to survey research. Ann R Coll Surg Engl. 2013;95(1):5-7. doi:10.1308/003588413X13511609956372

Finkel EJ, Eastwick PW, Reis HT. Best research practices in psychology: Illustrating epistemological and pragmatic considerations with the case of relationship science. J Pers Soc Psychol . 2015;108(2):275-97. doi:10.1037/pspi0000007

Harris LR, Brown GTL. Mixing interview and questionnaire methods: Practical problems in aligning data . Practical Assessment, Research, and Evaluation. 2010;15 (1). doi:10.7275/959j-ky83

Fincham JE. Response rates and responsiveness for surveys, standards, and the Journal . Am J Pharm Educ . 2008;72(2):43. doi:10.5688/aj720243

Shiyab W, Ferguson C, Rolls K, Halcomb E. Solutions to address low response rates in online surveys .  Eur J Cardiovasc Nurs . 2023;22(4):441-444. doi:10.1093/eurjcn/zvad030

Latkin CA, Mai NV, Ha TV, et al. Social desirability response bias and other factors that may influence self-reports of substance use and HIV risk behaviors: A qualitative study of drug users in Vietnam. AIDS Educ Prev. 2016;28(5):417-425. doi:10.1521/aeap.2016.28.5.417

American Psychological Association.  Ethical principles of psychologists and code of conduct .

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Introduction to Research Methods

5 quantitative research and surveys.

In the previous chapter we talked about different types of research. There we categorized research into three categories: secondary, applied, and academic. However, there are other ways to group research. One common distinction is between quantitative and qualitative research. Neither type is better or worse that the other, they’re simply different approaches to building new knowledge that can be more or less appropriate based on the goals of your research. In this chapter we’ll focus on quantitative research, and more specifically using surveys to build quantitative data. In the next chapter we’ll focus on qualitative research and talk about interviews. Those are the two most common ways of collecting data in the social sciences, although they are not the only ways (more are described in chapter 7).

5.1 Quantitative or qualitative

As was mentioned above, two types of research are quantitative and qualitative. We’ll describe qualitative research more in the next chapter, but it’s worth pausing to talk about both types here before we go into the specifics on either. The choice of which to use should be driven by the research question you’re pursuing. The most readily apparent difference will be in the data you’ll use. At its most basic level, quantitative data is numbers, whereas qualitative data focuses on words. You can analyze the numeric data using techniques which give you statistically robust answers to your questions. Qualitative data involves interpreting the words of respondents, and can provide answers all the same, but they won’t often carry the same statistical evidence.

5.2 Using a survey

Let’s say you’re setting out to research what makes people happy. You’ve read the previous chapter, so you know the importance of defining your concepts. You’ve done that, and decided that the best way to understand how happy people are is to have them rate their level of happiness on a scale of 0-10. Great, but how are you going to get people to give you that information?

One way would be with a survey. A survey involves collecting data from a group of people by administering a standardized questionnaire. The questionnaire, or survey can be written documentation that is administered either in person (door-to-door), on paper (through the mail), by phone, or online. Survey research is a quantitative method that uses predetermined questions that aim to describe or explain features of a very large group or groups.

Surveys are really common. The way we know how many people are in the United States is based on a survey (US Census). How do we know the unemployment rate in the United States? A survey. How do TV stations call the election as soon as polls close, before 98% of ballots have been counted? Surveys.

In this chapter I’ll try to walk you through the steps of developing a survey project. Let’s jump to the conclusion though, to make sure that we’re all on the same page. Below is a portion of a survey. It’s not the whole thing, just a few of the questions included on that survey. But that’s a survey, a form that asks respondents set questions and provides them space to answer them. There’s lots of ways you can deliver the survey, there’s a limitless number of questions you can ask, and you’ll still have to figure out who you’re going to survey. But that’s the end goal.

We’re going to talk about a lot of minutiae in this chapter, but it’s all important to doing a good survey.

5.3 Why survey?

The reason that researchers and society rely on surveys is because of their ability to provide information, even for people not asked to provide data. If you’re developing your happiness survey, are you going to gather the information from all 8 billion people on the planet? Imagine trying to get data about everyone just in your own neighborhood. That would be a challenge, to put it kindly. Luckily, you don’t have to. Researchers have developed ways to understand everyone based on the characteristics of a few .

Surveys, if correctly developed, can provide reliable information that can be generalized to the population. Generalizability means that what we learn from the sample (53% of the respondents like vanilla ice cream) can be related to everyone (53% of people likes vanilla ice cream). To formulate projections or broad-based conclusions, you need to conduct surveys that represent the public at large, which means including relevant groups (based on race, gender, age group, etc.) from a larger population in the correct proportions. We’ll talk more about populations and samples in a future chapter, but it’s worth knowing what’s possible.

Because of the ability to generalize the information we gather, surveys are often a cost effective form of research. The physical production of a survey questionnaire is relatively inexpensive. Even if you mail your survey and have to pay for postage, it’s far less expensive and time consuming than it would be to interview dozens or hundreds of respondents in person. However, it can take significant time to identify who you want to survey.

While surveys are advantageous in many respects, they’re not perfect! One of the biggest drawbacks with surveys is their inflexibility, which is to say, your questionnaire is your only means of collecting data. All you have is their answers to the questions, and if they don’t understand or interpret on of your questions correctly you might not get good data back. In addition, people aren’t great at accurately answering survey questions, even when they try. We’ll talk about ways to address that concern later though.

5.4 How to survey

There are a variety of ways in which a survey can be administered. Remember, how you conduct your survey—as well as when you administer it—will impact your response rate . Ideally, 100% of the people you send your survey to would send it back, but that will never happen. People are busy, they lose them, or they might just not care. Even offering a reward (money, gift cards, etc.) wont guarantee people will take the time to respond. Thus, it’s important to structure your survey in a way that helps to secure as many responses as possible. The response rate just refers to the percentage of people that the survey was sent to that you recieve a response from.

A traditional way to administer surveys is in the form of a self-administered questionnaire, a paper-and-pencil survey, in which participants are given a set of questions they respond to and then return either by mail or in person. Alternatively, it is increasingly common and cost effective to administer surveys online. Alternatively, you can also see people in person (door to door or standing in public spaces) and ask them to fill out the questionnaire.

The 2020 U.S. Census, for example, includes options to respond by mail, phone or online in an effort to produce a high response rate and more complete data.

5.5 Types of Surveys

An additional considerations is how you want to administer your survey with respect to time, and whether you want to survey your population at a single point or over an extended period.

One option is a cross-sectional survey , which is given at just one point in time. Such a survey will tell you how things were for the respondents at the particular time, such as who they would support in the presidential election in the third week of August. The respondents answers might change before and after the survey, so you’re essentially getting a snapshot of views and feelings at that moment.

A longitudinal survey , on the other hand, lets you make observations over an extended period of time. There are several types of longitudinal surveys you can conduct. Three of the mains ones are: trend, panel, and cohort surveys.

Trend surveys, as the name suggests, measure trends. If you conduct a trend survey, you are studying how people’s thoughts and views change over time. For example, if you want to know how Americans’ views on healthcare have changed over the past 10 years, you would ask the same questions to people at different points in time over a 10-year period. You wouldn’t have to survey the same people each time because as a researcher you’re more interested in the generalized trend over time than who is being sampled each time. What is critical is asking the same question worded the same way, to capture changes in people’s views.

A panel survey, on the other hand, focuses on the same people each time the survey is administered. An example of this would be if you studied the effects of exercise on 100 kids over a 10-year period beginning at age 12 and following them until they are 22. These surveys can produce impressive results. On the downside, however, panel surveys are costly and difficult to manage. It’s hard to keep track of dozens of people over a period of many years as they relocate, change jobs or names and pass away. As such, panel surveys take considerable resources and investment to administer.

A third type of longitudinal survey is a cohort survey, in which you identify a category of people of interest then randomly select individuals from within that category to survey over time. It is important to note that you don’t have to pick the same people each year; however, the people you do pick must fall into the same categories that you have previously selected. For instance in 1951 the British Doctors Study began by studying people who were exposed to smoking to understand whether it had an impact on the likelihood of lung cancer. They matched people who did smoke to non-smokers, and planned to continue tracking those two groups until 2001. However, it only took until 1956 for them to find convincing evidence that smoking increased cancer rates.

Which type of survey is best for you? It depends on the nature of your research project and the questions you’re trying to answer. Generally speaking, longitudinal surveys give us more information about trends, tendencies, opinions or ideas over a long period of time. Cross-sectional surveys have limited explanatory power because they only capture one moment. For instance, if I do a survey and find that healthier people are more likely to report riding their bike, do they bike because they’re healthy or are they healthy because they bike? We can’t tell just from that survey. However, if we survey the same people multiple times and see how biking and health change over time we can better identify the causal effect.

So why don’t we make every survey longitudinal? Because they can be costly and difficult to administer, and your research work may not require a temporal data analysis. Getting a high response rate on one survey is difficult, getting people to respond multiple times just compounds the problem. What’s important is that you understand the pros and cons of each type of survey and use the method that will produce, for you, the most meaningful data.

5.6 Writing Effective Questions

With survey’s it isn’t enough to just ask a question. You have to ask the right question. To get good information you have to be aware of all the ways your question could be misunderstood or could produce unreliable information. And first and foremost, you have to be aware that the thing you’re studying (humans) are complicated. We lie. We answer incorrectly. We randomly guess and answer questions we don’t have an answer for. We’re not very good at assessing ourselves. That’s why everyone makes the joke about 75% of drivers believing they’re above average drivers.

Let’s work through some of the things that can go wrong in your survey questions.

It is critical to avoid creating questions that could prompt respondents to give a socially desirable answer instead of an accurate one. In research, social desirability refers to the idea that respondents will try to answer questions in a way that will present them in a favorable light. Imagine asking a survey question regarding sensitive topics like abortion or racism to respondents. Some people might answer those types of questions without stating their true belief in order to appear socially acceptable, and so in general we know people will under report these behaviors. That makes them more difficult to study through a survey, but not impossible.

To take one example, what do you do if you want to run a survey on binge drinking at colleges? Simply asking a direct question like below probably wont produce accurate results.

One approach would be to ask the question multiple ways, giving people more opportunities to answer. And you’ll likely want to be specific in your questions. People might not consider themselves to be binge drinkers (or unfaithful, or racist, etc.), but if you ask whether they’ve had more than 5 drinks in one sitting the past week, they may be more honest about that without realizing that might make them a binge drinker. And asking factual-behavior based questions may help to avoid incorrect self appraisals.

Another problematic survey question is one that contains multiple questions, yet is posed as one single question. This is called a double-barreled question and has the potential to confuse the respondent. Take the question below for example about recent movies. If someone answers ‘Yes’ is it because they think new movies are too long or unoriginal, or both? We don’t know, it might be both, it might just be one. If you find the word “and” or “or” in your question, seriously think about breaking it into two separate questions.

As we’ve discussed, people will lie and may do a poor job of accurately reporting information on themselves. In addition, there is no one single understanding of many terms, such as toughness, happiness, risk-aversion, etc. As such, you can’t just ask a respondent if they’re “tough” and expect to get an accurate response. A better strategy might be to ask multiple overlapping questions related to toughness, which together will help to approximate their personality.

You might expect people that are kind or optimistic will respond the same to every question, but that rarely happens. Changing the direction of a question from a positive wording to a negative wording can really shift how people evaluate themselves. For instance, asking whether someone is considerate, and someone is not considerate can produce opposite reactions. People typically aren’t kind or unkind, they exist on a spectrum between those two extremes. Asking multiple questions helps to identify where they exist within that continuum. For instance, see the questions below on toughness, which are pulled from the International Personality Item Pool , a database of survey questions that can be used to measure different personality traits. Taking these questions together and using them to measure whether someone is very tough, or sorta tough, or not tough, will give a more accurate result.

If you choose to only ask some questions about issues that only a few of your respondents have had experience with or may find relevant, it’s a good idea to use a filter question in your survey. A filter question is designed to identify some subset of survey respondents who are asked additional questions that are not relevant to the entire sample. Online surveys make filter questions a lot easier, because you can manually control what questions respondents see based on their answers. In the example below, we have to trust that the respondent understands whether to skip the next question or not.

You also may want to make sure that your respondents are reading the questions. Let’s be honest, we’ve all filled out a survey and just started randomly checking boxes to get it done faster. You can add an attention filter by telling the respondent which option to choose, to make sure they’re taking the time to answer accurately. Once you see who gets the attention filter question wrong, you can remove their answers from the final data, since you won’t know whether they answered any of the other questions correctly.

5.7 Response Options

So, you’ve created clear, concise, and understandable survey questions, but have you put much thought into your response options? Response options are the answers that you provide to the people taking your survey. Researchers can choose from a number of response options, but like everything else in surveys there’s no one right option for all questions. The best option for any question will be determined by the purposes of the research and the question being asked.

5.7.1 close-ended vs. open-ended

One crucial consideration is whether your questions will be close-ended or open-ended. A close-ended question means the respondent must choose between a limited number of pre-determined responses to the question. Close-ended questions are often used in quantitative research because the responses can be counted up more readily (55% of respondents said Yes to supporting free puppies for all, etc.).

When designing responses to close-ended questions, it’s important to ensure that the responses offered are both exhaustive and mutually exclusive . Making responses exhaustive means that every possible answer that a respondent could have can fit into one of the responses. When responses are mutually exclusive, on the other hand, there are no possible answers a respondent could have that might fit into more than one category simultaneously. Imagine a survey in which respondents are asked how many children they have. They can select from the following responses: “Zero”; “One”; “Two”; “Three”; and “Four or More”. The responses are exhaustive because whether the respondent has no children or fifty children, there is an accurate response for them to choose. The responses are mutually exclusive as well because no matter how many children they have, there is only one accurate response. Making response options both exhaustive and mutually exclusive helps ensure that every respondent can answer questions effectively and helps improve the accuracy of the data collected by reducing errors. If the responses can’t be mutually exclusive you can also allow respondents to choose multiple options.

Survey questions can also be open-ended , meaning the respondent has the opportunity to answer the question in their own words, without pre-determined response options. Open-ended questions have the advantage of allowing the respondent to share more detailed information, and to share opinions or information that the researcher might not have thought to ask about. On the other hand, analysis of open-ended questions can be more difficult because the responses are harder to measure. Open ended questions also take a lot more time from your respondents and can lead to fatigue, so they should generally be used sparingly.

Giving people only the options to select yes or no can make it difficult for respondents to answer honestly. Do you like to break the rules? You might think sometimes, if you really need to, but you don’t break the rules all the time. So would you say yes or no? Giving people a range of responses will allow them to give a more accurate response.

One common response option for close-ended survey questions is known as the Likert scale. A Likert scale allows a respondent to evaluate a statement using a range of possible options. This range is balanced, with an equal number of positive and negative choices, and often includes a neutral option. Likert scales most commonly measure agreement and disagreement, and often have five or seven response options, though they could conceivably include any number of choices. See the examples below.

Alternatively, respondents can be give the option to rate their agreement or reaction to a question using numeric options such as 0-5, 0-10, 0-100, etc.. Respondents may feel that they fall somewhere in between strongly agreeing and somewhat agreeing, so numeric responses allow them more freedom, however you wont know what a person thinks a 7 versus an 8 is in that case.

When using a Likert Scale, or a similar response option, researchers should be careful and intentional about whether to choose a neutral option, such as the “Neither Agree nor Disagree” option mentioned above. Doing so can encourage respondents to engage in related behaviors such as fence-sitting and floating. Fence-sitting refers to a respondent choosing a neutral option, even when they have an opinion. Floating refers to the opposite, when a respondent chooses an opinion that they don’t hold because there isn’t a neutral option. Both have the potential to influence a survey’s data, so researchers should be careful to anticipate whether one or the other might be a problem, and whether a neutral option is appropriate for a particular question.

5.9 Ready to start?

After reading this chapter you might realize there is a lot more nuance to designing surveys than you previously thought. With all these options and variables, how can the average researcher know they’ve designed the best survey for their particular research? One crucial step they can take is to conduct pre-testing. Pre-testing , as the name suggests, refers to sending out the survey to a sample of people before the actual research is conducted. Doing so can help the researcher understand how the respondents interact with the survey, including how long it takes, what questions are confusing or unclear, and if any of your questions are controversial. In this way, pre-testing is a necessary and invaluable way for researchers to identify problems with their surveys before the research is conducted.

5.10 After the Survey

So you’ve run your survey. What does the data tell you, aren’t the answers jumping out at you? A survey is just the data collection – it won’t tell you anything anything on its own. The first thing you’ll need to do is code your survey so that it’s ready for analysis. The survey that was shown at the beginning of the chapter was done on pen and paper, so it had to be manually entered into a spreadsheet for analysis. As we discussed, quantitative research generally means using numbers and statistical techniques, so all those question you asked have to be converted. Look at the “code sheet” used to code that survey below.

Once the answers get coded into a spreadsheet, your data is ready for analysis. We’ll talk about the steps of that analysis in future chapters though, don’t worry. For now, you’re done with the survey, and we’ll move to another prominent method – interviews.

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Why use surveys?

Survey research methods.

• Conducting market research surveys
• Common mistakes with market research surveys?

The different types of survey methods

Survey tools for your survey method, what can businesses do with these types of surveys, how to write a research survey (free example templates), try qualtrics for free, types of market research surveys.

20 min read There are different types of survey research you can run, but the majority of research is conducted with just a handful of research survey methods. We explore what they are and how to use them.

What is a market research survey?

A market research survey is a way of getting feedback directly from the people who have the ultimate say in your organization’s success: your customers.

Unlike focus groups or interviews, market research surveys allow you to get detailed feedback at scale — from behaviors to overall experiences — and in a standardized format. Also, as the data is easy to process, you can quickly turn it into actionable insights .

Surveys are used to collect primary research, which means market research data that you collect yourself. The other type is secondary data, which is obtained from other sources, for example census data.

Surveys are among the most popular methods of primary market research, since they can be used to gather qualitative and quantitative research on market trends, and they can cover a huge range of respondents across your customer base. They’re also a format familiar to many people.

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Surveys are ultimately about understanding your target audience, but they can go beyond your customer base. They can be taken by anyone — employees, potential future customers, and even those who don’t want to engage with your business (helping you to identify the ones that do).

However, a survey isn’t a stand-alone solution. It can work alongside other survey methods, such as focus groups, field studies, observation, and market analysis, to help you get a clear picture of your market and decide what direction to take.

But with all these different types of survey methods, and some being better than others in specific areas (e.g. data quality, collecting feedback), where should you start?

To get the best out of each survey research type, consider what you can invest in terms of:

• Time: How quickly do you need the survey research? Do you have time to conduct research?
• Money: Do you have the budget to invest in research overheads?
• Knowledge of analytics: Are you trained to interpret the collected data? If not, do you have a partner you can work with to get the insights you need?
• Research expertise: Do you have clearly defined problems or challenges that you want to explore or understand through surveys?
• Technology capability: Is your survey software up to the task of analyzing the data?
• Your audience’s response: Is it likely that your audience will respond? What survey types (online surveys, etc.) would they be most receptive to?
• Slow responses: Do you have a strategy in place to avoid low response rates?

Conducting market research surveys: best practices

Today’s market research industry is advancing rapidly, thanks in part to new technologies which make it easier to conduct market research, and offer more power and sophistication when it comes to analyzing your data.

Data-driven research is the standard across market research and other disciplines, and within the sector competition between brands is driving progress towards better and better market research tools. Beyond customer satisfaction, demographic questions and competitive analysis, today’s tools can dive deeper into your data, unearthing key drivers behind trends and even providing aggregated data on emotions and attitudes in customer feedback.

However, none of these technological advances can replace humans. To conduct market research successfully, you need to be able to combine tech with insight, intelligence and intuition, especially when you’re dealing directly with target customers, for example during a phone interview or when you’re approaching existing customers whose relationship to your brand needs to be maintained.

As we’ll see in this guide, market research can be used in a huge range of contexts, including brand tracking, customer experience research, employee experience programs, and of course product development. Whichever application you’re looking at, it’s essential to prepare thoroughly before sending out your surveys.

• Make sure your research question has been formulated and agreed by everyone involved in the project
• Develop a communications plan to maximize the chances of people engaging with your survey, including introductions, publicity, reminders and follow-up
• Consider using pre-testing before you fully launch your survey to thoroughly road-test it and iron out any issues
• Close the loop – after the study is complete and actions have been taken, let participations know how their contribution helped
• Consider a research panel for future surveys, either one you’ve built yourself or one managed by a third party provider

What are some common mistakes with market research surveys?

With the right survey tools and appropriate support from your survey platform provider, everything should go smoothly, even if you’re not an expert at doing your own market research. However, there are a few things to watch out for.

Choosing the wrong people to survey

Figuring out who you’re going to survey in the first place may seem like an obvious first step and not one you need to spend much time on. But in fact it’s possible to get it wrong, survey the wrong people and end up running a market research study with unreliable data. This is sometimes called ‘sample framing error’

Getting your sample size wrong

If your sample is too small, you run the risk of getting a sample group that doesn’t adequately reflect your target population. This can throw your entire market research survey off course. But if the sample is too large, you spend time and money on research that doesn’t add significant value. Have a look at our sample size calculator to help determine the right sample size for your market research surveys.

Using the wrong kinds of analysis

Do you know your conjoint analysis from your T-test? Understanding the basic types of statistical tests you can use to analyze market research survey data is essential if you’re not using a survey tool with built-in analytics. You’ll need to match the kind of data you’re collecting to the analysis method you choose in order to get accurate insights from your market research surveys.

Writing confusing survey questions

Survey questions aren’t like the questions we use in everyday speech, or even like the ones we ask in formal writing. They need to be highly specific, include appropriate context, and be free of any kind of descriptive or persuasive element that might introduce bias. For a primer on writing great market research survey questions, see our guide to great survey questions

You should choose your survey method based on your target audience, distribution capabilities, and the questions you want answered. For example, interviews are far more personal and explorative by nature, but they’re difficult and costly to scale. Online surveys, on the other hand, have far greater reach and much more affordable — but you lose the opportunity to connect with respondents. Let’s go through the different types and how you can use them.

Online surveys

Online surveys are accessible to any participant across the globe, providing they have an internet connection. You can create online surveys using survey platforms and distribute them via email using a link, or respondents can go directly to the online survey and complete it.

Paper surveys

Paper surveys (or written surveys) are printed surveys filled in by hand. This method works well if respondents have enough time (and incentive) to complete the survey, and the researcher is happy to manually collect the data before collating and interpreting the answers.

Mail surveys

Mail surveys provide exceptional geographical coverage as they can be printed off and sent via the post. However, as recipients need to return the surveys for counting, it’s recommended that you include a pre-paid returns envelope in the original envelope, otherwise you’ll have lower response rates.

Telephone surveys

Telephone surveys involve asking respondents a series of questions over the phone. It’s a popular survey method as it’s convenient for researchers and doesn’t require a lot of capital to do. However, researchers may need to invest time to set up interviews with participants and take notes during the process.

In-person interviews / face-to-face surveys

In-person interviews and face-to-face surveys are great opportunities to get more insightful and valuable responses from participants. You can quickly find out why they think and feel the way that they do, providing an unbiased view of a subject or issue. However, like telephone surveys, they require a lot of time to set up and gather data.

Panel surveys

Panel surveys use a pre-selected group of people as the sample, so that the research can be carried out quickly. It presents a happy medium between the speed and quality of research data.

Based on the type of survey method you choose, here are the types of tools you need and can use for each:

A good internet connection is required for participants to access online surveys, though mobile devices data plans mean that most people can connect to the internet easily.

A good survey software platform is needed to give you full functionality and flexibility, so your online surveys can be customized and optimized. However, businesses can get more for their money with a survey software system that does more for the company.

For example, the Qualtrics XM Platform™ is a best-of-breed experience operating system for experience management. It brings all your operational and experience data together from across the organization to help create and improve experiences for employees, customers, prospects and more. It automatically updates records, has an in-built analytics engine and can handle research projects, from start to finish, in a few clicks.

All you need are paper, ink, pens and clipboards — but due to environmental and sustainability concerns, particularly paper waste and ink pollution, you may want to opt for a more digitized solution.

For mail surveys, the resources and concerns are the same as with paper surveys — but the main difference is distribution.

Ultimately, you need a reliable postal service that can deliver to your target audience. It also becomes costly if you want to include international respondents.

As long as you have good connectivity and network coverage, telephone surveys are straightforward. That said, survey calls can last a long time, so if you plan to include international audiences, ensure you can afford the calling costs.

The only requirement for in-person interviews and face-to-face surveys is a venue to hold them in.

These require participants to be available at the time of the research. Traditionally, third-party generated research panels are available as a service to companies that don’t have access to the audiences they need.

The surveys we explored can be used for four purposes in any business:

1. Market surveys

These help you understand who’s out there, what they want, and how you can best meet their needs.

Market description surveys

Purpose: to determine the size and relative market share of the market. Such studies provide key information about market growth, competitive positioning, and tracking share of the market .

Market profiling / segmentation surveys

Purpose: to identify who the customers are , who they are not, and why they are or are not your customers. This is often a descriptive market segmentation and market share analysis.

Stage in the purchase process / tracking surveys

Where is the customer in the adoption process? This information shows Market Awareness – Knowledge – Intention – Trial – Purchase – Repurchase of the product.

2.   Customer experience surveys

This kind of survey helps you put yourself in the customer’s shoes and look at your business from their perspective.

Customer intention – purchase analysis surveys

Purpose: Directed at understanding the current customer. What motivates the customer to move from interest in the product to actual purchase? This is key to understanding customer conversion, commitment, and loyalty .

Customer attitudes and expectations surveys

Purpose: Used to direct advertising and improve customer conversion, commitment, and loyalty. Does the product meet customer expectations ? What attitudes have customers formed about the product and/or company?

Learn how you can set up and run customer attitudes and use surveys

Sales lead generation surveys

Purpose: Sales lead generation surveys are for

• assuring timely use and follow-up of sales leads
• qualifying sales leads (thereby saving valuable sales force time)
• providing more effective tracking of sales leads

Customer trust / loyalty / retention analysis surveys

Purpose: Especially helpful for high-priced consumer goods with a long decision and purchase processes (time from need recognition to purchase), this type of study explores the depth of consumer attitudes formed about the product and/or company.

Salesforce effectiveness surveys

Purpose: A combination of measures that focus on the sales activities, performance, and effectiveness in producing the desired and measurable effect or goal. Often measured as a 360-degree survey completed by the salesperson, the client (evaluating the sales call), and the supervisor responsible for evaluating the salesperson.

Customer service surveys

Purpose: Akin to customer satisfaction surveys, customer service surveys instead focus in detail on the actual customer service that was received, the process involved in receiving that service, and the evaluation of the participants in the service process.

Customer service representative (CSR) surveys

Purpose: CSRs often exhibit frustration, burnout, and high turnover . Surveys focus on CSR retention, reducing costs, and increasing the quality of customer relationships.

Attitudes, burnout, turnover, and retention: CSRs hold attitudes that reflect on their job-related activities including:

• the allocation of time
• solutions to customer needs
• how to improve their job
• best practices
• how well internal departments help customers

3. Product surveys

As part of product development, surveys help you find out what features, benefits and attributes appeal most to your customers, and how best to package your product, experience or service.

New product, service or experience concept analysis surveys

Purpose: Concept test studies are appropriate in the initial screening of new product concepts . Likes and dislikes about the concept and evaluation of acceptability and likelihood of purchase are especially useful measures.

Concept optimization, demand estimation, and cost analysis surveys (conjoint analysis)

Purpose: Determines an optimal bundle of features and benefits, and estimates associated demand. This kind of survey develops market share estimates of market potential for the alternative potential products.

Habits and practices, or attitude and usage surveys

Purpose: Directed at understanding usage situations, including how, when, and where the product is used. Habits and practices studies sometimes include a real or virtual pantry audit. Attitude and usage studies are used to understand consumer attitudes towards the product category and to life in general. They also look at product and brand usage, including how, when and where the product is used.

Product satisfaction surveys (attribute, features, promised benefits)

Purpose: Evaluation of the product’s promised bundle of benefits (both tangible and image). Are expectations created for the product by advertising, packaging , and the product appearance fulfilled by the product?

Competitive benchmarking surveys

Purpose: A “best practices” study of “how does the market view us relative to the competition?” Competitive positioning analyses often compare the attributes and benefits that make up the product using multidimensional scaling. These analyses also include an evaluation of key competitors, looking at the same KPIs and attributes as product satisfaction surveys.

Sales forecasting and market tracking surveys

Purpose: Sales forecasting and market tracking studies can include expert opinion (experts estimate the market), judgmental bootstrapping (expert-based rules describing how to use available secondary market information), conjoint analysis (estimation of consumer intentions based on product attributes that are important in the decision), and intentions evaluations (consumer self-reported intentions of future purchases).

Price setting surveys and elasticity of demand analysis

Purpose: Price surveys estimate the elasticity of demand and show optimal price points, including prices too low or too high. Price surveys may estimate the demand for different product or service segments, or different usage situations.

4. Brand surveys

A survey can help you understand how consumers perceive your brand and what values and ideas they associate with it. You can explore what value your brand has and whether people would choose you over competitors in your market niche.

Brand equity analysis surveys

Purpose: What is the psychological value that a brand holds in the marketplace? Brand equity is a composite of brand awareness , brand quality, brand associations, and brand loyalty measures.

Advertising value identification and analysis surveys

Purpose: Advertising value analysis focuses on mapping the hierarchical attributes, benefits, and values that are associated with and portrayed by an advertisement. Means-end analysis is often part of this type of study.

Advertising message effectiveness surveys (media and message)

Purpose: Message effectiveness testing identifies the impressions, feelings, and effectiveness in moving the respondent to a desired goal (increased awareness, more product information, trial, repeat purchase).

Once you know the right type of survey to run, the next step is to write a survey that your respondents will love to take!

Survey methods can be used to help collect data on real business issues and help you answer questions. Qualtrics supports customer surveys on every channel, at every journey stage to get you answers for more informed decisions.

We’ve put together a range of survey example templates that you can use for free to help you get started:

• Employee satisfaction survey template
• Employee exit survey template
• Customer satisfaction (CSAT) survey template
• Ad testing survey template
• Brand awareness survey template
• Product pricing survey template
• Product research survey template
• Employee engagement survey template
• Customer service survey template
• NPS survey template
• Product package testing survey template
• Product features prioritization survey template

In addition, for large-scale research studies, Qualtrics offers market research services to help with everything from questionnaire design and survey methods, to implementation and analysis.

Related resources

Post event survey questions 10 min read, best survey software 16 min read, close-ended questions 7 min read, survey vs questionnaire 12 min read, response bias 13 min read, double barreled question 11 min read, likert scales 14 min read, request demo.

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18 Different Types of Survey Methods + Pros & Cons

There are many reasons why surveys are important. Surveys help researchers find solutions, create discussions, and make decisions. They can also get to the bottom of the really important stuff, like, coffee or tea? Dogs or cats? Elvis or The Beatles? When it comes to finding the answers to these questions, there are 18 different types of survey methods to use.

Create your first survey, form, or poll now!

18 Different Types of Survey Methods

Different surveys serve different purposes, which is why there are a number of them to choose from. “What are the types of surveys I should use,” you ask? Here’s a look at the 18 types of survey methods researchers use today.

1. Interviews

Also known as in-person surveys or household surveys, this used to be one of the most popular types of survey to conduct. Researchers like them because they involve getting face-to-face with individuals. Of course, this method of surveying may seem antiquated when today we have online surveying at our fingertips. However, interviews still serve a purpose. 

Researchers conduct interviews when they want to discuss something personal with people. For example, they may have questions that may require extensive probing to uncover the truth. Sure, some interviewees may be more comfortable answering questions confidentially behind a keyboard. However, a skilled interviewer is able to put them at ease and get genuine responses. They can often go deeper than you may be able to using other surveying methods. 

Often, in-person interviews are recorded on camera. This way, an expert can review them afterward. They do this to determine if the answers given may be false based on an interviewee’s change in tone. A change in facial expressions and body movements may also be a signal they pick up on. 

2. Intercept Surveys

While interviews tend to choose respondents and have controls in place, intercept surveys (or “man on the spot”) surveys are conducted at certain locations or events. This involves having an interviewer, or multiple interviewers, scoping out an area and asking people, generally at random, for their thoughts or viewpoints on a particular topic. 

3. Focus Groups

These types of surveys are conducted in person as well. However, focus groups involve a number of people rather than just one individual. The group is generally small but demographically diverse and led by a moderator. The focus group may be sampling new products, or to have a discussion around a particular topic, often a hot-button one. 

The purpose of a focus group survey is often to gauge people’s reaction to a product in a group setting or to get people talking, interacting—and yes, arguing—with the moderator taking notes on the group’s behavior and attitudes. This is often the most expensive survey method as a trained moderator must be paid. In addition, locations must be secured, often in various cities, and participants must be heavily incentivized to show up. Gift cards in the $75-100 range for each survey participant are the norm.   

4. Panel Sampling

Recruiting survey-takers from a panel maintained by a research company is a surefire way to get respondents. Why? Because people have specifically signed up to take them. The benefit of these types of surveys for research, of course, is there you can be assured responses. In addition, you can filter respondents by a variety of criteria to be sure you’re speaking with your target audience.

The downside is data quality. These individuals get survey offers frequently. So, they may rush through them to get their inventive and move on to the next one. In addition, if you’re constantly tapping into the same people from the same panel, are you truly getting a representative sample?

5. Telephone Surveys

Most telephone survey research types are conducted through random digit dialing (RDD). RDD can reach both listed  and  unlisted numbers, improving sampling accuracy. Surveys are conducted by interviewers through computer-assisted telephone interviewing (CATI) software. CATI displays the questionnaire to the interviewer with a rotation of questions.  

Telephone surveys started in the 1940s. In fact, in a  recent blog , we recount how the predictions for the 1948 presidential election were completely wrong because of sampling bias in telephone surveys. Rising in popularity in the late 50s and early 60s when the telephone became common in most American households, telephone surveys are no longer a very popular method of conducting a survey. Why? Because many people refuse to take telephone surveys or simply are not answering calls from a number they don’t recognize.

6. Post-Call Surveys

If a telephone survey is going to be conducted, today it is usually a post-call survey. This is often accomplished through IVR, or interactive voice response. IVR means there is no interviewer involved. Instead, customers record answers to pre-recorded questions using numbers on their touch-tone keypads. If a question is open-ended, the interviewee can respond by speaking and the system records the answer. IVR surveys are often deployed to measure how a customer feels about a service they just received. For example, after calling your bank, you may be asked to stay on the line to answer a series of questions about your experience.

Most post-call surveys are either  NPS surveys  or customer satisfaction (CSAT) surveys. The former asks the customer “How likely are you to recommend our organization to a f riend or family based on your most recent interaction?” while the CSAT survey asks customers “How satisfied are you with the results of your most recent interaction?”.   NPS survey results reflect how the customer feels about the brand, while CSAT surveys a re all about individual agent and contact center performance.   

7. SMS Text Surveys

Many people rarely using their phone to talk anymore, and ignore calls from unknown numbers. This has given rise to the SMS (Short Messaging Service) text survey. SMS surveys are delivered via text to people who have opted in to receive notifications from the sender. This means that there is usually some level of engagement, improving response rates. The one downside is that questions typically need to be short, and answers are generally 1-2 words or simply numbers (this is why many NPS surveys, gauging customer satisfaction, are often conducted via SMS text). Be careful not to send too many text surveys, as a person can opt-out just as easily, usually by texting STOP.

8. Mail-in Surveys / Postal Surveys

These are delivered right to respondents’ doorsteps! Mail surveys were frequently used before the advent of the internet when respondents were spread out geographically and budgets were modest. After all, mail-in surveys didn’t require much cost other than the postage. 

So are mail-in surveys going the way of the dinosaur? Not necessarily. They are still occasionally more valuable compared to different methods of surveying. Because they are going to a specific name and home address, they often feel more personalized. This personalization can prompt the recipient to complete the survey. 

They’re also good for surveys of significant length. Most people have short attention spans, and won’t spend more than a few minutes on the phone or filling out an online survey. At least, not without an incentive! However, with a mail-in survey, the person can complete it at their leisure. They can fill out some of it, set it aside, and then come back to it later. This gives mail-in surveys a relatively high response rate.

9. Kiosk Surveys

These surveys happen on a computer screen at a physical location. You’ve probably seen them popping up in stores, hotel lobbies, hospitals, and office spaces. These days, they’re just about anywhere a researcher or marketer wants to collect data from customers or passers-by.  Kiosk surveys  provide immediate feedback following a purchase or an interaction. They collect responses while the experience is still fresh in the respondent’s mind. This makes their judgment more trustworthy. Below is an example of a SurveyLegend kiosk survey at McDonald’s. The kiosk survey collects information, thanks the respondent for their feedback, and then resets for the next customer. Read how to  create your own kiosk survey here .

10. Email Surveys

Email surveys are one of the most effective surveying methods as they are delivered directly to your audience via their online account. They can be used by anyone for just about anything, and are easily customized for a particular audience. Another good thing about email surveys is you can easily see who did or did not open the survey and make improvements to it for a future send to increase response rates. You can also A/B test subject lines, imagery, and so on to see which is more effective. SurveyLegend offers dozens of different types of online survey questions, which we explore in our blog  12 Different Types of Survey Questions and When to Use Them (with Examples) .

11. Pop-up Surveys

A pop-up survey is a feedback form that pops up on a website or app. Although the main window a person is reading on their screen remains visible, it is temporarily disabled until a user interacts with the pop-up, either agreeing to leave feedback or closing out of it. The survey itself is typically about the company whose site or app the user is currently visiting (as opposed to an intercept survey, which is an invitation to take a survey hosted on a different site).

A pop-up survey attempts to grab website visitors’ attention in a variety of ways, popping up in the middle of the screen, moving in from the side, or covering the entire screen. While they can be intrusive, they also have many benefits. Read about the  benefits of pop-up surveys here .

12. Embedded Surveys

The opposite of pop-up surveys, these surveys live directly on your website or another website of your choice. Because the survey cannot be X’ed out of like a pop-up, it takes up valuable real estate on your site, or could be expensive to implement on someone else’s site. In addition, although the  embedded survey  is there at all times, it may not get the amount of attention a pop-up does since it’s not “in the respondent’s face.”

13. Social Media Surveys

There are more than  3.5 billion people  are using social media worldwide, a number projected to increase to almost 4.5 billion in 2025. This makes social media extremely important to marketers and researchers. Using platforms such as Facebook, Twitter, Instagram, and the new Threads, many companies and organizations send out social media surveys regularly. Because people check their social media accounts quite regularly, it’s a good way to collect responses and monitor changes in satisfaction levels or popular opinion. Check out our blog on  social media surveys  for more benefits and valuable tips.

14. Mobile Surveys

Mobile traffic has now overtaken desktop computers as the most used device for accessing the internet, with more than 54% of the share. But don’t fret – you don’t have to create an entirely new survey to reach people on their phones or tablets. Online poll makers like SurveyLegend are responsive, so when you create a desktop version of a survey, it automatically becomes mobile-friendly. The survey renders, or displays, on any device or screen regardless of size, with elements on the page automatically rearranging themselves, shrinking, or expanding as necessary. Learn more about our  responsive surveys .

15. Mobile App Surveys

Today, most companies have a mobile app. These can be an ideal way to conduct surveys as people have to willingly download your app; this means, they already have a level of engagement with your company or brand making them more likely to respond to your surveys.

16. QR Code Surveys

QR Code or QRC is an abbreviation of “Quick Response Code.” These two-dimensional encoded images, when scanned, deliver hidden information that’s stored on it. They’re different from barcodes because they can house a lot more information, including website URLs, phone numbers, or up to 4,000 characters of text. The recent QR code comeback provides a good opportunity for researchers to collect data. Place the QR code anywhere – on flyers, posters, billboards, commercials – and all someone had to do is scan it with the mobile device to have immediate access to a survey. Read more about the  benefits of QR code surveys .

17. Delphi Surveys

A Delphi survey is a structured research method used to gather the collective opinions and insights of a panel of experts on a particular topic. The process involves several rounds of questionnaires or surveys. Each round is designed to narrow things down until a consensus or hypothyses can be formed. One of the key features of the Delphi survey research is that participants are unknown to each other, thereby eliminating influence.

18. AI Surveys

Artificial intelligence is the latest types of survey method. Using AI, researchers allow the technology to ask survey questions. These “Chatbots” can even ask follow-up questions on the spot based on a respondent’s answer. There can be drawbacks, however. If a person suspects survey questions are coming from AI, they may be less likely to respond (or may respond incorrectly to mess with the AI). Additionally, AI is not good with emotions, so asking sensitive questions in an emotionless manner could be off putting to people.  Read more about AI Surveys .

Online Surveys: Ideal for Collecting Data and Feedback

That’s not all. People can take online surveys just about anywhere thanks to mobile devices. The use of these devices across age groups is balancing out as well. Check out smartphone use by age group below.

With more and more people accessing the internet through their mobile devices, now you can reach teens while they’re between classes and adults during their subway commute to work. Can’t say that for those other types of surveys !

Online surveys are also extremely cost-efficient. You don’t have to spend money on paper, printing, postage, or an interviewer. This significantly reduces set-up and administration costs. This also allows researchers and companies to send out a survey very expeditiously. Additionally, many online survey tools provide in-depth analysis of survey data. This saves you from having to spend money on further research once the survey is complete. 

Researchers have their pick of options when it’s time to survey people. Which method you choose may depend upon cost, reach, and the types of questions.

Now, you may be wondering, “ Where can I make free surveys ?” You can get started with free online surveys using SurveyLegend! He re are a few things that make SurveyLegend the ideal choice for different types of surveys for research ( or for fun) .

• When it comes to surveys, brief is best to keep respondents attention. So, SurveyLegend automatically collects some data, such as the participant’s location, reducing the number of questions you have to ask.
• People like eye candy and many surveys are just plain dull. SurveyLegend offers beautifully rendered pre-designed surveys that will get your participant’s attention – and keep it through to completion!
• Today, most people take surveys on mobile devices. Often surveys desktop surveys don’t translate well, resulting in a high drop-off rate. SurveyLegend’s designs are responsive, automatically adjusting to any screen size.

What’s your favorite method of surveying people? (Hey… that’s a good topic for a survey!) Sound off in the comments!

Frequently Asked Questions (FAQs)

The 10 most common survey methods are online surveys, in-person interviews, focus groups, panel sampling, telephone surveys, post-call surveys, mail-in surveys, pop-up surveys, mobile surveys, and kiosk surveys.

Benefits of online surveys include their ability to reach a broad audience and that they are relatively inexpensive.

Kiosk surveys are surveys on a computer screen at the point of sale.

A focus group is an in-person interview or survey involving a group of people rather than just one individual. The group is generally small but demographically diverse, and led by a moderator. 

Jasko Mahmutovic

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Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.

Handbook of eHealth Evaluation: An Evidence-based Approach [Internet].

Chapter 13 methods for survey studies.

Francis Lau .

13.1. Introduction

The survey is a popular means of gauging people’s opinion of a particular topic, such as their perception or reported use of an eHealth system. Yet surveying as a scientific approach is often misconstrued. And while a survey seems easy to conduct, ensuring that it is of high quality is much more difficult to achieve. Often the terms “survey” and “questionnaire” are used interchangeably as if they are the same. But strictly speaking, the survey is a research approach where subjective opinions are collected from a sample of subjects and analyzed for some aspects of the study population that they represent. On the other hand, a questionnaire is one of the data collection methods used in the survey approach, where subjects are asked to respond to a predefined set of questions.

The eHealth literature is replete with survey studies conducted in different health settings on a variety of topics, for example the perceived satisfaction of ehr systems by ophthalmologists in the United States ( Chiang et al., 2008 ), and the reported impact of emr adoption in primary care in a Canadian province ( Paré et al., 2013 ). The quality of eHealth survey studies can be highly variable depending on how they are designed, conducted, analyzed and reported. It is important to point out there are different types of survey studies that range in nature from the exploratory to the predictive, involving one or more groups of subjects and an eHealth system over a given time period. There are also various published guidelines on how survey studies should be designed, reported and appraised. Increasingly, survey studies are used by health organizations to learn about provider, patient and public perceptions toward eHealth systems. As a consequence, the types of survey studies and their methodological considerations should be of great interest to those involved with eHealth evaluation.

This chapter describes the types of survey studies used in eHealth evaluation and their methodological considerations. Also included are three case examples to show how these studies are done.

13.2. Types of Survey Studies

There are different types of survey study designs depending on the intended purpose and approach taken. Within a given type of survey design, there are different design options with respect to the time period, respondent group, variable choice, data collection and analytical method involved. These design features are described below ( Williamson & Johanson, 2013 ).

13.2.1. The Purpose of Surveys

There are three broad types of survey studies reported in the eHealth literature: exploratory, descriptive, and explanatory surveys. They are described below.

• Exploratory Surveys – These studies are used to investigate and understand a particular issue or topic area without predetermined notions of the expected responses. The design is mostly qualitative in nature, seeking input from respondents with open-ended questions focused on why and/or how they perceive certain aspects of an eHealth system. An example is the survey by Wells, Rozenblum, Park, Dunn, and Bates (2014) to identify organizational strategies that promote provider and patient uptake of phr s.
• Descriptive Surveys – These studies are used to describe the perception of respondents and the association of their characteristics with an eHealth system. Perception can be the attitudes, behaviours and reported interactions of respondents with the eHealth system. Association refers to an observed correlation between certain respondent characteristics and the system, such as prior eHealth experience. The design is mostly quantitative and involves the use of descriptive statistics such as frequency distributions of Likert scale responses from participants. An example is the survey on change in end user satisfaction with cpoe over time in intensive care ( Hoonakker et al., 2013 ).
• Explanatory Surveys – These studies are used to explain or predict one or more hypothesized relationships between some respondent characteristics and the eHealth system. The design is quantitative, involving the use of inferential statistics such as regression and factor analysis to quantify the extent to which certain respondent characteristics lead to or are associated with specific outcomes. An example is the survey to model certain residential care facility characteristics as predictors of ehr use ( Holup, Dobbs, Meng, & Hyer, 2013 ).

13.2.2. Survey Design Options

Within the three broad types of survey studies one can further distinguish their design by time period, respondent group, variable choice, data collection and analytical method. These survey design options are described below.

• Time Period – Surveys can take on a cross-sectional or longitudinal design based on the time period involved. In cross-sectional design the survey takes place at one point in time giving a snapshot of the participant responses. In longitudinal design the survey is repeated two or more times within a specified period in order to detect changes in participant responses over time.
• Respondent Group – Surveys can involve a single or multiple cohorts of respondents. With multiple cohorts they are typically grouped by some characteristics for comparison such as age, sex, or eHealth use status (e.g., users versus non-users of emr ).
• Variable Choice – In quantitative surveys one needs to define the dependent and independent variables being studied. A dependent variable refers to the perceived outcome that is measured, whereas an independent variable refers to a respondent characteristic that may influence the outcome (such as age). Typically the variables are defined using a scale that can be nominal, ordinal, interval, or ratio in nature ( Layman & Watzlaf, 2009 ). In a nominal scale, a value is assigned to each response such as 1 or F for female and 2 or M for male. In an ordinal scale, the response can be rank ordered such as user satisfaction that starts from 1 for very unsatisfied to 4 for very satisfied. Interval and ratio scales have numerical meaning where the distance between two responses relate to the numerical values assigned. Ratio is different from interval in that it has a natural zero point. Two examples are weight as a ratio scale and temperature as an interval scale.
• Data Collection – Surveys can be conducted by questionnaire or by interview with structured, semi-structured or non-structured questions. Questionnaires can be administered by postal mail, telephone, e-mail, or through a website. Interviews can be conducted in-person or by phone individually or in groups. Pretesting or pilot testing of the instrument should be done with a small number of individuals to ensure its content, flow and instructions are clear, consistent, appropriate and easy to follow. Usually there are one or more follow-up reminders sent to increase the response rate.
• Analytical Method – Survey responses are analyzed in different ways depending on the type of data collected. For textual data such qualitative analyses as content or thematic analysis can be used. Content analysis focuses on classifying words and phrases within the texts into categories based on some initial coding scheme and frequency counts. Thematic analysis focuses on identifying concepts, relationships and patterns from texts as themes. For numeric data, quantitative analysis such as descriptive and inferential statistics can be used. Descriptive statistics involves the use of such measures as mean, range, standard deviation and frequency to summarize the distribution of numeric data. Inferential statistics involve the use of a random sample of data from the study population to make inferences about that population. The inferences are made with parametric and non-parametric tests and multivariate methods. Pearson correlation, t -test and analysis of variance are examples of parametric tests. Sign test, Mann-Witney U test and χ 2 are examples of non-parametric tests. Multiple regression, multivariate analysis of variance, and factor analysis are examples of multivariate methods ( Forza, 2002 ).

13.3. Methodological Considerations

The quality of survey studies is dependent on a number of design parameters. These include population and sample, survey instrument, sources of bias, and adherence to reporting standards. These considerations are described below ( Williamson & Johanson, 2013 ).

13.3.1. Population and Sample

For practical reasons, survey studies are often done on a sample of individuals rather than the entire population. Sampling frame refers to the population of interest from which a representative sample is drawn for the study. The two common strategies used to select the study sample are probability and non-probability sampling. These are described below.

• Probability sampling – This is used in descriptive and explanatory surveys where the sample selected is based on the statistical probability of each individual being included under the assumption of normal distribution. They include such methods as simple random, systematic, stratified, and cluster sampling. The desired confidence level and margin of error are used to determine the required sample size. For example, in a population of 250,000 at 95% confidence level and a ±5% margin of error, a sample of 384 individuals is needed (Research Advisors, n.d.).
• Non-probability sampling – This is used in exploratory surveys where individuals with specific characteristics that can help understand the topic being investigated are selected as the sample. They include such non-statistical methods as convenience, snowball, quota, and purposeful sampling. For example, to study the effects of the Internet on patients with chronic conditions one can employ purposeful sampling where only individuals known to have a chronic disease and access to the Internet are selected for inclusion.

13.3.2. Survey Instrument

The survey instrument is the tool used to collect data from respondents on the topic being investigated. Ideally one should demonstrate that the survey instrument chosen is both valid and reliable for use in the study. Validity refers to whether the items (i.e., predefined questions and responses) in the instrument are accurate in what they intend to measure. Reliability refers to the extent to which the data collected are reproducible when repeated on the same or similar groups of respondents. These two constructs are elaborated below.

• Validity – The four types of validity are known as face, content, criterion, and construct validity. Face and content validity are qualitative assessments of the survey instrument for its clarity, comprehensibility and appropriateness. While face validity is typically assessed informally by non-experts, content validity is done formally by experts in the subject matter under study. Criterion and construct validity are quantitative assessments where the instrument is measured against other schemes. In criterion validity the instrument is compared with another reputable test on the same respondents, or against actual future outcomes for the survey’s predictive ability. In construct validity the instrument is compared with the theoretical concepts that the instrument purports to represent to see how well the two align with each other.
• Reliability – The tests for reliability include test-retest, alternate form and internal consistency. Test-retest reliability correlates results from the same survey instrument administered to the same respondents over two time periods. Alternate form reliability correlates results from different versions of the same instrument on the same or similar individuals. Internal consistency reliability measures how well different items in the same survey that measure the same construct produce similar results.

13.3.3. Sources of Bias

There are four potential sources of bias in survey studies. These are coverage, sampling, non-response, and measurement errors. These potential biases and ways to minimize them are described below.

• Coverage bias – This occurs when the sampling frame is not representative of the study population such that certain segments of the population are excluded or under-represented. For instance, the use of the telephone directory to select participants would exclude those with unlisted numbers and mobile devices. To address this error one needs to employ multiple sources to select samples that are more representative of the population. For example, in a telephone survey of consumers on their eHealth attitudes and experience, Ancker, Silver, Miller, and Kaushal (2013) included both landline and cell phone to recruit consumers since young adults, men and minorities tend to be under-represented among those with landlines.
• Sampling bias – This occurs when the sample selected for the study is not representative of the population such that the sample values cannot be generalized to the broader population. For example, in their survey of provider satisfaction and reported usage of cpoe , Lee, Teich, Spurr, and Bates (1996) reported different response rates between physicians and nurses, and between medical and surgical staffs, which could affect the generalizability of the results. To avoid sampling bias one should clearly define the target population and sampling frame, employ systematic methods such as stratified or random sampling to select samples, identify the extent and causes of response differences, and adjust the analysis and interpretation accordingly.
• Non-response bias – This occurs when individuals who responded to the survey have different attributes than those who did not respond to the survey. For example, in their study to model nurses’ acceptance of barcoded medication administration technology, Holden, Brown, Scanlon, and Karsh (2012) acknowledged their less than 50% response rate could have led to non-response bias affecting the accuracy of their prediction model. To address this error one can offer incentives to increase response rate, follow up with non-respondents to find out the reasons for their lack of response, or compare the characteristics of non-respondents with respondents or known external benchmarks for differences ( King & He, 2005 ). Adjustments can then be made when the cause and extent of non-response are known.
• Measurement bias – This occurs when there is a difference between the survey results obtained and the true values in the population. One major cause is deficient instrument design due to ambiguous items, unclear instructions, or poor usability. To reduce measurement bias one should apply good survey design practices, adequate pretesting or pilot testing of the instrument, and formal tests for validity and reliability. An example of good Web-based eHealth survey design guidelines is the Checklist for Reporting Results of Internet E-Surveys ( cherries ) by Eysenbach (2004) . The checklist has eight item categories and 31 individual items that can be used by authors to ensure quality design and reporting of their survey studies.

13.3.4. Adherence to Reporting Standards

Currently there are no universally accepted guidelines or standards for reporting survey studies. In the field of management information systems ( mis ), Grover, Lee, and Durand (1993) published nine ideal survey methodological attributes for analyzing the quality of mis survey research. In their review of ideal survey methodological attributes, Ju, Chen, Sun, and Wu (2006) found two frequent problems in survey studies published in three top mis journals to be the failure to perform statistical tests for non-response errors and not using multiple data collection methods. In healthcare, Kelly, Clark, Brown, and Sitzia (2003) published a checklist of seven key points to be covered when reporting survey studies. They are listed below:

• Explain the purpose of the study with explicit mention of the research question.
• Explain why the research is needed and mention previous work to provide context.
• Provide detail on how study was done that covers: the method and rationale; the instrument with its psychometric properties and references to original development/testing; sample selection and data collection processes.
• Describe and justify the analytical methods used.
• Present the results in a concise and factual manner.
• Interpret and discuss the findings.
• Present conclusions and recommendations.

In eHealth, Bassi, Lau, and Lesperance (2012) published a review of survey-based studies on the perceived impact of emr in physician office practices. In the review they used the 9-item assessment tool developed by Grover and colleagues (1993) to appraise the reporting quality of 19 emr survey studies. Using the 9-item tool a score from 0 to 1 was assigned depending on whether the attribute was present or absent, giving a maximum score of 9. Of the 19 survey studies appraised, the quality scores ranged from 0.5 to 8. Over half of the studies did not include a data collection method, the instrument and its validation with respect to pretesting or pilot testing, and non-respondent testing. Only two studies scored 7 or higher which suggested the reporting of the 19 published emr survey studies was highly variable. The criteria used in the 9-item tool are listed below.

• Report the approach used to randomize or select samples.
• Report a profile of the sample frame.
• Report characteristics of the respondents.
• Use a combination of personal, telephone and mail data collection methods.
• Append the whole or part of the questionnaire in the publication.
• Adopt a validated instrument or perform a validity or reliability analysis.
• Perform an instrument pretest.
• Report on the response rate.
• Perform a statistical test to justify the loss of data from non-respondents.

13.4. Case Examples

13.4.1. clinical informatics governance for ehr in nursing.

Collins, Alexander, and Moss (2015) conducted an exploratory survey study to understand clinical informatics ( ci ) governance for nursing and to propose a governance model with recommended roles, partnerships and councils for ehr adoption and optimization. The study is summarized below.

• Setting – Integrated healthcare systems in the United States with at least one acute care hospital that had pioneered enterprise-wide ehr implementation projects and had reached the Health Information Management Systems Society ( himss ) Analytics’ emr Adoption Model ( emram ) level 6 or greater, or were undergoing enterprise-wide integration, standardization and optimization of existing ehr systems across sites.
• Population and samples – Nursing informatics leaders in the role of an executive in an integrated healthcare system who could offer their perspective and lessons learned in their organization’s clinical and nursing informatics governance structure and its evolution. The sampling frame was the himss Analytics database that contains detailed information on most u.S. healthcare organizations and their health it status.
• Design – A cross-sectional survey conducted through semi-structured telephone interviews with probing questions.
• Measures – The survey had four sections: (a) organizational characteristics; (b) participant characteristics; (c) governance structure; and (d) lessons learned. Questions on governance covered decision-making, committees, collaboration, roles, and facilitators/barriers for success in overall and nursing-specific ci governance.
• Analysis – Grounded theory techniques of open, axial and selective coding were used to identify overlapping themes on governance structures and ci roles. Data were collected until thematic saturation in open coding was reached. The ci structures of each organization were drawn, compared and synthesized into a proposed model of ci roles, partnerships and councils for nursing. Initial coding was independently validated among the researchers and group consensus was used in thematic coding to develop the model.
• Results – Twelve nursing executives (made up of six chief nursing information officers, four directors of nursing informatics, one chief information officer, and one chief ci officer) were interviewed by phone. For analysis 128 open codes were created and organized into 18 axial coding categories where further selective coding led to four high-level themes for the proposed model. The four themes (with lessons learned included) identified as important are: inter-professional partnerships; defining role-based levels of practice and competence; integration into existing clinical infrastructure; and governance as an evolving process.
• Conclusion – The proposed ci governance model can help understand, shape and standardize roles, competencies and structures in ci practices for nursing, as well as be extended to other domains.

13.4.2. Primary Care EMR Adoption, Use and Impacts

Paré et al. (2013) conducted a descriptive survey study to examine the adoption, use and impacts of primary care emr s in a Canadian province. The study is summarized below.

• Setting – Primary care clinics in the Canadian Province of Quebec that had adopted electronic medical records under the provincial government’s emr adoption incentive and accreditation programs.
• Population and samples – The population consisted of family physicians as members of the Quebec Federation of General Practitioners that practice in primary care clinics in the province. The sample had three types of physician respondents that: (a) had not adopted emr (type-1); (b) had emr in their clinic but were not using it to support their practice (type-2); or (c) used emr in their clinic to support their practice (type-3).
• Design – A cross-sectional survey in the form of a pretested online questionnaire in English and French accessible via a secure website. E-mail invitations were sent to all members followed by an e-mail reminder. With a sampling frame of 9,166 active family physicians in Quebec, 370 responses would be needed to obtain a representative sample with a 95% confidence interval and a margin of error of ±5%.
• Measures – For all three respondent types the measures were clinic and socio-demographic profiles and comments. For type-2 and type-3 respondents, the measures were emr brand and year of implementation. For type-1 the measures were barriers and intent to adopt emr . For type-2 the measures were reasons and influencing factors for not using emr , and intent to use emr in future. For type-3 the measures were emr use experience, level and satisfaction, ease of use with advanced emr features, and individual/organizational impacts associated with emr use.
• Analysis – Descriptive statistics in frequencies, per cent and mean Likert scores were used on selected measures. Key analyses included comparison of frequencies by: socio-demographic and clinic profiles; barrier and adoption intent; emr feature availability and use; and comparison of mean Likert scores for satisfaction and individual and organizational impacts. Individual impacts included perceived efficiency, quality of care and work satisfaction. Organizational impacts included effects on clinical staff, the clinic’s financial position, and clients.
• Results – Of 4,845 invited physicians, 780 responded to the survey (16% response rate) that was representative of the population. Just over half of emr users reported the high cost and complexity in emr acquisition and deployment as the main barriers. Half of non-users reported their clinics intended to deploy emr in the next year. emr users made extensive use of basic emr features such as clinical notes, lab results and scheduling, but few used clinical decision support and data sharing features. For work organization, emr s addressed logistical issues with paper systems. For care quality, emr s improved the quality of clinical notes and safety of care provided but not clinical decision-making. For care continuity, emr s had poor ability to transfer clinical data among providers.
• Conclusion – emr impacts related to a physician’s experience where the perceived benefits were tied to the duration of emr use. Health organizations should continue to certify emr products to ensure alignment with the provincial ehr .

13.4.3. Nurses’ Acceptance of Barcoded Medication Administration Technology

Holden and colleagues (2012) conducted an explanatory survey study to identify predictors of nurses’ acceptance of barcoded medication administration ( bcma ) in a u.S. pediatric hospital. The study is summarized below.

• Setting – A 236-bed free standing academic pediatric hospital in the midwestern U.S. that had recently adopted bcma . The hospital also had cpoe , a pharmacy information system and automated medication-dispensing units.
• Population and Sample – The population consisted of registered nurses that worked at least 24 hours per week at the hospital. The sample consisted of nurses from three care units that had used bcma for three or more months.
• Design – A cross-sectional paper survey with reminders was conducted to test the hypothesis that bcma acceptance would be best predicted by a larger set of contextualized variables than the base variables in the Technology Acceptance Model ( tam ). A multi-item scales survey instrument, validated in previous studies with several added items, was used. The psychometric properties of the survey scales were pretested with 16 non-study nurses.
• Measures – Seven bcma -related perceptions: ease of use, usefulness for the job, non-specific social influence, training, technical support, usefulness for patient care, and social influence from patients/families. Responses were 7-point scales from not-at-all to a-great-deal. Also tracked were variables for age in five categories, as well as experience measured as job tenure in years and months. Two bcma acceptance variables: behavioural intention to use and satisfaction.
• Analysis – Regression of all subsets of perceptions to identify the best predictors of bcma acceptance using five goodness-of-fit indicators (i.e., R 2 , root mean square error, Mallow’s Cp statistics, Akaike information criterion, and Bayesian information criterion). An a priori α criterion of 0.05 was used and 95% confidence intervals were computed around parameter estimates.
• Results – Ninety-four of 202 nurses returned a survey (46.5% response rate) but 11 worked less than 24 hours per week and were excluded, leaving a final sample of 83 respondents. Nurses perceived moderate ease of use and low usefulness of bcma . They perceived moderate or higher social influence to use bcma , and were moderately positive about bcma training and technical support. Behavioural intention to use bcma was high but satisfaction was low. Behavioural intention to use bcma was best predicted by perceived ease of use, non-specific social influence and usefulness for patient care (56% variance explained). Satisfaction was best predicted by perceived ease of use, usefulness for patient care and social influence from patients/families (76% variances explained).
• Conclusion – Predicting bcma acceptance benefited from using a larger set of perceptions and adapting variables.

13.5. Summary

This chapter introduced three types of surveys, namely exploratory, descriptive and explanatory surveys. The methodological considerations addressed included population and sample, survey instrument, variable choice and reporting standards. Three case examples were also included to show how eHealth survey studies are done.

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This publication is licensed under a Creative Commons License, Attribution-Noncommercial 4.0 International License (CC BY-NC 4.0): see https://creativecommons.org/licenses/by-nc/4.0/

• Cite this Page Lau F. Chapter 13 Methods for Survey Studies. In: Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.
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• Introduction
• Types of Survey Studies
• Methodological Considerations
• Case Examples

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Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews).

The case study research method originated in clinical medicine (the case history, i.e., the patient’s personal history). In psychology, case studies are often confined to the study of a particular individual.

The information is mainly biographical and relates to events in the individual’s past (i.e., retrospective), as well as to significant events that are currently occurring in his or her everyday life.

The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies.

Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

This makes it clear that the case study is a method that should only be used by a psychologist, therapist, or psychiatrist, i.e., someone with a professional qualification.

There is an ethical issue of competence. Only someone qualified to diagnose and treat a person can conduct a formal case study relating to atypical (i.e., abnormal) behavior or atypical development.

 Famous Case Studies

• Anna O – One of the most famous case studies, documenting psychoanalyst Josef Breuer’s treatment of “Anna O” (real name Bertha Pappenheim) for hysteria in the late 1800s using early psychoanalytic theory.
• Little Hans – A child psychoanalysis case study published by Sigmund Freud in 1909 analyzing his five-year-old patient Herbert Graf’s house phobia as related to the Oedipus complex.
• Bruce/Brenda – Gender identity case of the boy (Bruce) whose botched circumcision led psychologist John Money to advise gender reassignment and raise him as a girl (Brenda) in the 1960s.
• Genie Wiley – Linguistics/psychological development case of the victim of extreme isolation abuse who was studied in 1970s California for effects of early language deprivation on acquiring speech later in life.
• Phineas Gage – One of the most famous neuropsychology case studies analyzes personality changes in railroad worker Phineas Gage after an 1848 brain injury involving a tamping iron piercing his skull.

Clinical Case Studies

• Studying the effectiveness of psychotherapy approaches with an individual patient
• Assessing and treating mental illnesses like depression, anxiety disorders, PTSD
• Neuropsychological cases investigating brain injuries or disorders

Child Psychology Case Studies

• Studying psychological development from birth through adolescence
• Cases of learning disabilities, autism spectrum disorders, ADHD
• Effects of trauma, abuse, deprivation on development

Types of Case Studies

• Explanatory case studies : Used to explore causation in order to find underlying principles. Helpful for doing qualitative analysis to explain presumed causal links.
• Exploratory case studies : Used to explore situations where an intervention being evaluated has no clear set of outcomes. It helps define questions and hypotheses for future research.
• Descriptive case studies : Describe an intervention or phenomenon and the real-life context in which it occurred. It is helpful for illustrating certain topics within an evaluation.
• Multiple-case studies : Used to explore differences between cases and replicate findings across cases. Helpful for comparing and contrasting specific cases.
• Intrinsic : Used to gain a better understanding of a particular case. Helpful for capturing the complexity of a single case.
• Collective : Used to explore a general phenomenon using multiple case studies. Helpful for jointly studying a group of cases in order to inquire into the phenomenon.

Where Do You Find Data for a Case Study?

There are several places to find data for a case study. The key is to gather data from multiple sources to get a complete picture of the case and corroborate facts or findings through triangulation of evidence. Most of this information is likely qualitative (i.e., verbal description rather than measurement), but the psychologist might also collect numerical data.

1. Primary sources

• Interviews – Interviewing key people related to the case to get their perspectives and insights. The interview is an extremely effective procedure for obtaining information about an individual, and it may be used to collect comments from the person’s friends, parents, employer, workmates, and others who have a good knowledge of the person, as well as to obtain facts from the person him or herself.
• Observations – Observing behaviors, interactions, processes, etc., related to the case as they unfold in real-time.
• Documents & Records – Reviewing private documents, diaries, public records, correspondence, meeting minutes, etc., relevant to the case.

2. Secondary sources

• News/Media – News coverage of events related to the case study.
• Academic articles – Journal articles, dissertations etc. that discuss the case.
• Government reports – Official data and records related to the case context.
• Books/films – Books, documentaries or films discussing the case.

3. Archival records

Searching historical archives, museum collections and databases to find relevant documents, visual/audio records related to the case history and context.

Public archives like newspapers, organizational records, photographic collections could all include potentially relevant pieces of information to shed light on attitudes, cultural perspectives, common practices and historical contexts related to psychology.

4. Organizational records

Organizational records offer the advantage of often having large datasets collected over time that can reveal or confirm psychological insights.

Of course, privacy and ethical concerns regarding confidential data must be navigated carefully.

However, with proper protocols, organizational records can provide invaluable context and empirical depth to qualitative case studies exploring the intersection of psychology and organizations.

• Organizational/industrial psychology research : Organizational records like employee surveys, turnover/retention data, policies, incident reports etc. may provide insight into topics like job satisfaction, workplace culture and dynamics, leadership issues, employee behaviors etc.
• Clinical psychology : Therapists/hospitals may grant access to anonymized medical records to study aspects like assessments, diagnoses, treatment plans etc. This could shed light on clinical practices.
• School psychology : Studies could utilize anonymized student records like test scores, grades, disciplinary issues, and counseling referrals to study child development, learning barriers, effectiveness of support programs, and more.

How do I Write a Case Study in Psychology?

Follow specified case study guidelines provided by a journal or your psychology tutor. General components of clinical case studies include: background, symptoms, assessments, diagnosis, treatment, and outcomes. Interpreting the information means the researcher decides what to include or leave out. A good case study should always clarify which information is the factual description and which is an inference or the researcher’s opinion.

1. Introduction

• Provide background on the case context and why it is of interest, presenting background information like demographics, relevant history, and presenting problem.
• Compare briefly to similar published cases if applicable. Clearly state the focus/importance of the case.

2. Case Presentation

• Describe the presenting problem in detail, including symptoms, duration,and impact on daily life.
• Include client demographics like age and gender, information about social relationships, and mental health history.
• Describe all physical, emotional, and/or sensory symptoms reported by the client.
• Use patient quotes to describe the initial complaint verbatim. Follow with full-sentence summaries of relevant history details gathered, including key components that led to a working diagnosis.
• Summarize clinical exam results, namely orthopedic/neurological tests, imaging, lab tests, etc. Note actual results rather than subjective conclusions. Provide images if clearly reproducible/anonymized.
• Clearly state the working diagnosis or clinical impression before transitioning to management.

3. Management and Outcome

• Indicate the total duration of care and number of treatments given over what timeframe. Use specific names/descriptions for any therapies/interventions applied.
• Present the results of the intervention,including any quantitative or qualitative data collected.
• For outcomes, utilize visual analog scales for pain, medication usage logs, etc., if possible. Include patient self-reports of improvement/worsening of symptoms. Note the reason for discharge/end of care.

4. Discussion

• Analyze the case, exploring contributing factors, limitations of the study, and connections to existing research.
• Analyze the effectiveness of the intervention,considering factors like participant adherence, limitations of the study, and potential alternative explanations for the results.
• Identify any questions raised in the case analysis and relate insights to established theories and current research if applicable. Avoid definitive claims about physiological explanations.
• Offer clinical implications, and suggest future research directions.

5. Additional Items

• Thank specific assistants for writing support only. No patient acknowledgments.
• References should directly support any key claims or quotes included.
• Use tables/figures/images only if substantially informative. Include permissions and legends/explanatory notes.
• Provides detailed (rich qualitative) information.
• Provides insight for further research.
• Permitting investigation of otherwise impractical (or unethical) situations.

Case studies allow a researcher to investigate a topic in far more detail than might be possible if they were trying to deal with a large number of research participants (nomothetic approach) with the aim of ‘averaging’.

Because of their in-depth, multi-sided approach, case studies often shed light on aspects of human thinking and behavior that would be unethical or impractical to study in other ways.

Research that only looks into the measurable aspects of human behavior is not likely to give us insights into the subjective dimension of experience, which is important to psychoanalytic and humanistic psychologists.

Case studies are often used in exploratory research. They can help us generate new ideas (that might be tested by other methods). They are an important way of illustrating theories and can help show how different aspects of a person’s life are related to each other.

The method is, therefore, important for psychologists who adopt a holistic point of view (i.e., humanistic psychologists ).

Limitations

• Lacking scientific rigor and providing little basis for generalization of results to the wider population.
• Researchers’ own subjective feelings may influence the case study (researcher bias).
• Difficult to replicate.
• Time-consuming and expensive.
• The volume of data, together with the time restrictions in place, impacted the depth of analysis that was possible within the available resources.

Because a case study deals with only one person/event/group, we can never be sure if the case study investigated is representative of the wider body of “similar” instances. This means the conclusions drawn from a particular case may not be transferable to other settings.

Because case studies are based on the analysis of qualitative (i.e., descriptive) data , a lot depends on the psychologist’s interpretation of the information she has acquired.

This means that there is a lot of scope for Anna O , and it could be that the subjective opinions of the psychologist intrude in the assessment of what the data means.

For example, Freud has been criticized for producing case studies in which the information was sometimes distorted to fit particular behavioral theories (e.g., Little Hans ).

This is also true of Money’s interpretation of the Bruce/Brenda case study (Diamond, 1997) when he ignored evidence that went against his theory.

Breuer, J., & Freud, S. (1895).  Studies on hysteria . Standard Edition 2: London.

Curtiss, S. (1981). Genie: The case of a modern wild child .

Diamond, M., & Sigmundson, K. (1997). Sex Reassignment at Birth: Long-term Review and Clinical Implications. Archives of Pediatrics & Adolescent Medicine , 151(3), 298-304

Freud, S. (1909a). Analysis of a phobia of a five year old boy. In The Pelican Freud Library (1977), Vol 8, Case Histories 1, pages 169-306

Freud, S. (1909b). Bemerkungen über einen Fall von Zwangsneurose (Der “Rattenmann”). Jb. psychoanal. psychopathol. Forsch ., I, p. 357-421; GW, VII, p. 379-463; Notes upon a case of obsessional neurosis, SE , 10: 151-318.

Harlow J. M. (1848). Passage of an iron rod through the head.  Boston Medical and Surgical Journal, 39 , 389–393.

Harlow, J. M. (1868).  Recovery from the Passage of an Iron Bar through the Head .  Publications of the Massachusetts Medical Society. 2  (3), 327-347.

Money, J., & Ehrhardt, A. A. (1972).  Man & Woman, Boy & Girl : The Differentiation and Dimorphism of Gender Identity from Conception to Maturity. Baltimore, Maryland: Johns Hopkins University Press.

Money, J., & Tucker, P. (1975). Sexual signatures: On being a man or a woman.

Further Information

• Case Study Approach
• Case Study Method
• Enhancing the Quality of Case Studies in Health Services Research
• “We do things together” A case study of “couplehood” in dementia
• Using mixed methods for evaluating an integrative approach to cancer care: a case study

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Criterion Validity: Definition & Examples

Different methods of survey sampling

2022-02-05 Market Research

What are the different methods of survey sampling?

Determining your sample, or the group of people participating in your survey, is one of the most crucial steps of conducting it.

There are two main kinds of sampling techniques — probability and non-probability sampling. Learn about the specific types of sampling within these categories to help you with your next survey.

Probability sampling methods

With probability sampling, each element of the population has a definite, non-zero probability of being used in the sample. This method guarantees that the entire population is represented in that selection. There are several types of probability sampling methods, including:

Simple random sampling

Simple random sampling is the purest type of probability sampling. With this method, individuals are chosen randomly, giving each member of the population an equal chance of being selected as the subject.

Systematic sampling

In a systematic sample, individuals are selected at regular intervals. For example, every 10th person on the population list may be selected to participate. This method assures that the population is sampled evenly.

Stratified sampling

Before a stratified sample is taken, the population is divided into groups based on characteristics pertinent to the research, such as age or gender. The population is then randomly sampled within these specific strata. This complex method of sampling ensures each category of the population is represented in the sample.

Cluster sampling

With cluster sampling, every member of the population is assigned to a group known as a cluster. A sample of clusters is chosen using a probability method like random sampling, and only individuals within the sampled cluster are surveyed.

Multistage sampling

Multistage sampling uses several different probability sampling methods. For example, your sampling process may begin with cluster sampling. Then, you use simple random sampling to choose a subset of participants from each cluster to create the final sample.

Non-probability sampling methods

With non-probability sampling techniques, the sample is collected based on specific criteria, so not every member of the population has a chance of being selected. These sampling methods are often used for online surveys. The different types of non-probability sampling include:

Convenience sampling

In a convenience sample, individuals are selected for how easily accessible they are to the researcher. This method is typically used during preliminary research phases.

Quota sampling

Quota sampling is similar to stratified sampling, except it assigns a quota to each population subset, meaning that the sample must include a specific number of individuals from each group.

Judgment/purposive sampling

With judgment or purposive sampling, the researcher selects individuals for a specific quality relevant to the study. For example, if you want to study what it takes to graduate summa cum laude, you would survey individuals who graduated with that distinction.

Snowball sampling

In a snowball sample, you rely on your initial survey respondents to refer you to new participants.

Voluntary sampling

A voluntary sample is made up of people who volunteer to take part in the survey. Typically, these respondents have a strong interest in the survey topic.

Contact Cint for survey solutions

At Cint, our tools help you connect with survey respondents  to help complete your survey.  Contact us  to learn more.

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Standalone Regulatory Agreements for Product-Development Collaborations in the Medical Products Industry

• Original Research
• Open access
• Published: 31 May 2024

Cite this article

You have full access to this open access article

• Mary E Wilhelm   ORCID: orcid.org/0009-0002-6776-709X 1 ,
• Nancy Pire-Smerkanich 2 &
• Frances J Richmond 2  

Medical-product companies often outsource research and manufacturing needs to contracting or partnering organizations but then must manage a challenging patchwork of regulatory activities. A standalone regulatory agreement could clarify the relationships and responsibilities between companies working jointly on a single regulated product. This study explored the need for and current use of standalone regulatory agreements.

A survey instrument was developed using an implementation framework and disseminated to mid- to senior-level employees and consultants for sponsor and vendor companies in the medical products sector.

Of 294 respondents, about half, primarily from companies with more than 200 employees, were familiar with standalone regulatory agreements, and half of this subgroup had moved forward to implement them. Such agreements were considered beneficial to clarify regulatory roles and responsibilities, standardize regulatory expectations between the companies, and stimulate earlier discussion about joint regulatory strategies. However, the development of regulatory agreements appears challenged by the fact that such agreements are not required by regulatory agencies overseeing medical products and have no standardized templates, agency or industry guidance. Respondents whose organizations do not now use regulatory agreements either had not considered or did not see a need for a standalone agreement.

Conclusions

Standalone regulatory agreements are becoming more common but are not yet implemented fully by most companies. Their usefulness and content appeared to depend upon the type of partner, the complexity of the relationship and the availability of internal expertise and support.

Avoid common mistakes on your manuscript.

Introduction

Pharmaceutical development over the last few decades has evolved to take advantage of external contractors that conduct specialized activities [ 1 , 2 , 3 ]. Partnering with storage and distribution suppliers, Contract Development and Manufacturing Organizations (CDMOs), and Contract Research Organizations (CROs) can decrease clinical and production costs and reduce the need to hire and train new personnel. The importance of such relationships is reflected in the growth of specialist contractors that in clinical research alone now contribute to what has become a $40 Billion global industry [ 4 ].

Beginning interactions with CDMOs and CROs are typically transactional. The deliverables are usually determined before the relationship is established and the contracted agreements reflect the nature of an often-narrow service. With time, however, companies have become comfortable with contracts for a variety of more complicated relationships. These might include, for example, Quality Agreements governing the product’s ingredients and containers, Technical Agreements that detail the quality and testing of the product, and Supply Chain Agreements that define terms for pricing and payment, minimum and maximum purchase quantities, delivery lead times, product return policies, and liabilities when materials are lost [ 5 ]. Further, Clinical Trial Agreements typically define the responsibilities of the sponsor, CRO and clinical site, terms governing publication and intellectual property, and arrangements for record keeping, inspection, indemnification, and insurance [ 6 ]. To manage these types of partnerships, companies may alternatively use a Master Service Agreement (MSA) that “consolidates separate but related agreements between the same signing parties” [ 7 ]. The MSA will define more expectations- confidentiality, delivery requirements, dispute resolution, intellectual property rights and payment terms, for example- that each partner must satisfy to fulfill the contract.

However, more recently, the interactions between a sponsor and its partners have changed in ways that do not lend themselves to simpler contracts. Relationships through unrestricted grants with centers created for drug discovery, or partnerships with specialized CROs, academia and biotech companies, for example, may be less clearly defined, may involve risk-sharing and may change as new ideas and specialized technologies are introduced to address the increased complexities of drugs in development [ 2 , 3 , 8 , 9 ]. One particular concern is the way that the two organizations will contribute to the regulatory deliverables and filings related to that product during the time of the partnership, which often extends over many years. As the relationship evolves from early development to product approval, changing events and circumstances can affect the expectations of partners over time. Thus, their roles with respect to regulatory filings can be more difficult to capture in simple transactional contracts or high-level business agreements because they fail to cover important areas of responsibility and expectations.

Standalone regulatory agreements have the potential to address more directly the regulatory expectations between partners in joint ventures and mergers of some types. Some expected areas could include the preparation of submission documents, review of nonclinical and clinical research reports, attendance at health agency meetings, review of product labeling, advertising and promotion, and ownership of original submission documents and records. However, the use of regulatory agreements has not been described in any detail by current literature. We therefore have no clear picture of the extent to which regulatory agreements have been introduced and what regulatory requirements might be most important to address. Some companies may rely on other existing agreements to meet this need, but we do not know the extent to which such an approach has been used. We also have little insight into the previous experiences of companies in partnership agreements and whether they believe that a more comprehensive regulatory agreement would have been helpful. A primary goal of this research is to identify current views and experiences of individuals in companies conducting joint development programs that require some form of regulatory sharing. From this information, we discuss the potential role of stand-alone regulatory agreements and propose a framework for their content.

Materials and Methods

This study explored the views and experiences of mid- to senior-level employees at sponsor and vendor companies in the medical products sector whose experiences in drug development encompassed activities in regulatory, quality, clinical, or product development. Included also were consultants and individuals experienced with legal, financial, business development or alliance management activities during product development. Prior to this study, we explored the available literature systematically to identify whether any previous guidelines regarding regulatory agreements were available [ 10 ]. Further, no public database was found to identify systematically individuals who would be appropriate respondents. To assure a broad representation from companies of different sizes, participants were identified by title through LinkedIn networks, personal referrals, social networking platforms and professional associations. Respondents were considered to meet inclusion criteria if they worked at medical product companies in regulatory, clinical, or quality roles and had recent or current experience with the conduct of joint development programs. Interested respondents were encouraged to nominate others to participate.

A self-administered survey instrument was built with reference to an implementation framework described by Fixsen and coworkers [ 11 , 12 ], which divided implementation into Exploration, Installation, Initial Implementation and Final Implementation [ 13 ]. Its 42 questions were configured using multiple-choice, scaled, matrix, rank-ordered and open-text formats. A brief introduction defined what is meant by a regulatory agreement and asked respondents to provide answers based on their experiences with one recent company in which they worked. Questions were designed to solicit input on the current use or possible need for regulatory agreements between partnering companies, including vendor companies such as a CDMO or CRO, or a company and academia (Appendix A ). Three skip-logic branches were used to hide more detailed questions from participants whose answers to preliminary questions suggested little experience in a specialized area. The first branch divided participants who had heard of standalone regulatory agreements from those who had not. The next branch separated respondents who did not have collaborations with other companies or academic institutions from respondents who had investigated the use of standalone regulatory agreements from those who had not. A third branch separated respondents who had implemented or planned to implement regulatory agreements from those who did not move forward or had not investigated these agreements. A focus group of 8 participants from industry and academia critiqued the survey, which was then revised to address their suggestions.

The survey was deployed anonymously to 1194 potential participants using the web-based survey platform, Qualtrics ( http://www.qualtrics.com/ ); 294 started the survey and 244 completed at least one question for a response rate of 20% and a completion rate of 83%. An additional 50 participants accessed the survey using an anonymous link and completed at least one question for the combined total of 294 respondents. Respondents were allowed to skip questions so the number of respondents answering each question varied and is shown for each set of answers. Cumulative results were analyzed using descriptive statistics and cross-tabulations. Open text and comment fields were analyzed to identify themes or common elements. One question used a rank order format so that respondents could rank their preferences. A rank score was calculated by applying a weight to each response. Because this question used a 5-point scale, the number of responses where the option was ranked as 1 (or most likely) was multiplied by 5, as 2 was multiplied by 4, as 3 by 3, as 4 by 2, and as 5 by 1. The total weighted score for each option was summed and divided by the number of respondents, to get the final rank option, sorted from highest (1) to lowest (5).

Study Dissemination

Respondents ranged in experience and functional role; three-quarters were at or above the Director level and represented companies across a spectrum of sizes (Table  1 ). Most worked for sponsor companies (76%). The others were in consultancies (15%), clinical support organizations (6%), law firms or in-house counsel roles (1%) or other industry-related organizations (2%). 65% dealt with pharmaceuticals, 57% with biologics/biotechnology products, 33% with medical devices/diagnostics, and 32% with combination products. Many had experience with more than one product type, as reflected by total percentages much higher than 100%. 3% worked in other areas, which they identified as cell or gene therapies, cosmetics, dietary supplements, food additives, industrial chemical, and veterinary biologicals.

Companies with Regulatory Agreements

About half of the respondents had previously heard of standalone regulatory agreements developed as a separate document (yes: 54%; no: 46%) (Table  1 ). 40% of respondents who had heard about regulatory agreements had investigated and implemented the use of standalone regulatory agreements, whereas 12% were in the process of developing them and 34% had not investigated their use (Fig.  1 ). In addition, 8% of this group had investigated these types of agreements but did not go forward. Only 6% were not involved in collaborations with other companies or academic institutions.

Use of Regulatory Agreements with Business or Academic Partners. Please think about your collaboration projects with other pharmaceutical, biotechnology, or device companies or with an academic institute. Has your company investigated the use of standalone regulatory agreements for any of these collaborations? (number of responses = 151 of 152 respondents presented with this question)

Respondents structured a variety of relationships when they worked with other pharmaceutical, biologics/biotechnological, medical device, support-service and vendor companies, academic institutions, and consultancies. Most commonly, their partnerships were governed by formal agreements (55-87%) (Table  2 ). Preferred partner/vendor contracts governed less than 8% of relationships with their consultants and pharmaceutical, biotechnology and academic organizations but were somewhat more frequent for partnerships with device companies (11%) and support-service/vendor organizations (23%). Informal agreements and research grants were rare (< 5%) amongst commercial organizations. However, about 10% of academic agreements were informal and a further 19% were research grants.

Companies relied on different resources when first developing a regulatory agreement. Almost all identified that internal company experience/expertise was useful (91%) and most that the structure/contents of other contracts or scope of other partnerships were useful (85% and 77% respectively). Government documents and external consultants were regarded as useful by 56% and 54% of respondents respectively, but as not useful by 23%.

Respondents with regulatory agreements were asked if 6 development elements related to regulatory strategy, reviews and logistics were included in these initial agreements (Fig.  2 ). Respondents selected these choices in the following order: roles in regulatory submissions (86%); adherence to regulatory procedures (77%), development of regulatory strategy (74%); regulatory requests authoring, review, and approval (74%); attendance at agency meetings (56%); and postmarketing activities (56%). 14% identified “other” elements with responses related to documentation, compliance, responsibility, or communication.

Development Elements Included in Initial Regulatory Agreements. What development elements were included in the initial regulatory agreement? (choose all that apply) (number of responses = 70 from 79 respondents presented with this question)

The respondents were also asked if 4 elements related to regulatory reviews and 4 elements related to logistics were included in those initial agreements (Fig.  3 ). A majority chose all elements related to regulatory review: report review and approval (73%); timing for review/modification of agreement (60%); review and approval of labeling (59%); number and timing of review cycles for documents (54%). The 4 logistical elements were chosen by many: management of records (84%); governance and communication processes (77%); development of RACI matrices defining roles for Responsible, Accountable, Consulted, and Informed parties (63%); and roles and responsibilities to manage crisis (44%). Three respondents (4%) selected “other”, adding safety reporting and notifications of audits, inspections, and adverse events.

Review and Logistics Elements Included in Initial Regulatory Agreements. What review or logistics elements were included in the initial regulatory agreement? (choose all that apply) (number of responses = 70 from 79 respondents presented with this question)

When asked about additional elements that they would include in the next revision of their company’s regulatory agreement, 35 comments were received from 73 respondents presented with this question. Substantive comments were grouped into 4 themes- compliance; roles and responsibilities; document review; and processes (Table  3 ).

Companies without Regulatory Agreements

Respondents in companies without standalone regulatory agreements were asked why these agreements were not in place. The challenge of having another standalone agreement was chosen most often (26%) from a list of 5 suggested reasons (Fig.  4 ). Alternatively, some saw no need for such an agreement (23%), had not thought of it (18%) or felt that it was a good idea but had insufficient information (12%). Rarely chosen was the reason that the partner company saw no need for such an agreement (2%). Other was selected by 19%; their comments were grouped in 4 themes that are listed under Fig.  4 .

Reasons for Not Having Regulatory Agreements. What is the reason your company does not have standalone regulatory agreements? (number of responses = 164 of 191 respondents presented with this question)

Asked how regulatory elements are covered currently in the absence of regulatory agreements, most respondents pointed to other formal contracts or agreements such as Master Service Agreements (MSA) (83%) (Fig.  5 ) or identified that they used work orders or scope-of-work documents instead (45%). A small group identified that they employed informal agreements or relationships (13%), or that they required no regulatory agreements in their partnerships (5%). Other comments (11%) expanded on the same categories that were included in Fig.  5 .

How Companies Without Regulatory Agreements Cover Regulatory Requirements with Their Partners. How does your company ensure that regulatory requirements are covered in their current partnerships with other companies and vendors? (choose all that apply) (number of responses = 261 from166 respondents presented with this question)

When asked about hurdles that they might anticipate if they were to implement regulatory agreements (Fig.  6 ), most predicted that the greatest hurdles would be faced within their own companies rather than those of their partners. These internal hurdles included: resource limitations (69%); lack of templates (68%); unsupportive management (67%); no recognition of a need for such documents (64%); and lack of time to set up such agreements (62%). Least often identified was lack of internal expertise (38%). However, a lack of internal expertise was identified as the biggest perceived hurdle for the partnering company (38%) or academia (20%).

Impediments to Using Regulatory Agreements. What hurdles do you see in implementing the use of regulatory agreements with a business partner (pharmaceutical/biotechnology/device company) or an academic institution? (choose all that apply) (number of responses = 156 from 194 respondents presented with this question)

Additional Views from Respondents

All respondents were asked to rank 4 choices that might explain why we hear so little about the use of regulatory agreements (from 1 to 5, most to least likely) (Table  4 ). Most highly ranked was the choice that regulatory elements were covered in other contracts. However, closely ranked were: (2) the value of such agreements was unclear; and (3) the company had not thought about it. Least likely was the choice that informal relationships were sufficient (4). A few respondents offered other reasons, included in Table  4 .

Proposed Agreement Framework

Most respondents with regulatory agreements suggested that their initial regulatory agreements included most of the basic development, review, and logistics elements provided as options in the survey questions but added additional logistical and management elements to strengthen the contract in later iterations as indicated in the comment fields above. These many elements can be used to develop a generic framework for a regulatory agreement between partners with a specific focus on agreements that involve shared responsibilities for regulatory submissions. Some of these elements would be inappropriate for agreements with other partners, and additional elements might be added to address activities unanticipated by the checklist provided in Table  5 .

Today, medical product development depends on large teams of experts who contribute in different ways to business and regulatory decisions. The challenges of the COVID-19 pandemic have underlined the fragility of such relationships, as developers confronted challenges related to supply chains, working patterns and production needs [ 14 , 15 , 16 ]. Perhaps it was not surprising then, that half of the respondents surveyed here had heard about regulatory agreements, and a quarter, mostly from companies with more than 200 employees, had implemented them. In large companies, contractual relationships of many kinds are common, so developing standalone regulatory agreements is just one more way to establish a well-controlled development path shared between regulatory personnel in joint ventures when the responsibilities of two or more companies become deeply connected. Such a situation is common, for example, in biopharmaceutical companies, where one company develops a new drug but then partners with one or more larger companies to conduct clinical trials, manufacturing and eventual global commercialization.

This is not to say that such agreements should become a regulatory requirement. Rather they are a good solution for more complicated regulatory programs, as part of an armamentarium to clarify expectations between partners and meet regulatory requirements. These expectations include the US regulation, 21 CFR 312.52, Transfer of obligations to a contract research organization :

A sponsor may transfer responsibility for any or all of the obligations set forth in this part to a contract research organization. Any such transfer shall be described in writing [ 15 ].

The ICH Consensus Guideline, an addendum to the ICH E6(R1): Guideline for Good Clinical Practice ICH E6(R2), also includes the statement that:

A sponsor may transfer any or all of the sponsor’s trial-related duties and functions to a CRO, but the ultimate responsibility for the quality and integrity of the trial data always resides with the sponsor. The CRO should implement quality assurance and quality control. (Sect. 5 Sponsor: Sect. 5.2.1) [ 17 ].

However, the statements of regulatory authorities identify the sponsor’s ultimate responsibility for the conduct of the work. They do not specify how that requirement should be satisfied.

The stand-alone regulatory agreement has similar goals and structures when compared to its already well-accepted sister agreement, the quality agreement. FDA not only expects that companies will have quality agreements with key suppliers but has specified basic areas- documentation, change control, materials management, product specifications, and laboratory controls, for example- that such a document should address. Quality agreements should also clarify issues of compliance and communication between parties, which can be more challenging because the timing and depth of various work elements can change as time passes [ 18 , 19 , 20 ]. Agreements of these types usually serve as a starting point for defining the relationship but over time must be revisited to be sure that changing condition do not require a revision of terms.

The core value of a regulatory agreement is its promise to prevent miscommunication, unclear performance measures, wasted resources, and delays in decision making [ 21 , 22 , 23 ]. Regulatory agreements assume greater importance when the division of labor and extent of the collaborative activities become more complex. By covering a broad list of activities in one place, they help to avoid having a patchwork of items related to regulatory responsibilities in different documents, where they may be poorly visible to the affected regulatory personnel. They also provide an early opportunity to identify potentially non-compliant or unpromising partners. A key opportunity that regulatory agreements can offer is their ability to force the realignment of differing views regarding regulatory performance that might otherwise become contentious. However, not all potential issues are easy to capture even with a standalone agreement. These challenges relate to the more diffuse nature of the regulatory role, summarized by one respondent:

The details of regulatory agreements may not be fully considered. This is due, at least in part, to softer deliverables associated with regulatory. With other parties, such as CDMO/CROs, deliverables are tangible and straightforward to define.

Further, such agreements are less valuable if they lack enforcement clauses. Explicit statements are needed to specify corrective interventions or even legal actions that will be taken should the partner prove unreliable [ 24 , 25 ].

Respondents made clear that stand-alone regulatory agreements are not the only way to manage relationships, especially when partnerships or contracted activities are simpler. It was therefore not surprising to find that that small companies are less familiar with such agreements and may in fact have less need for them if they are at earlier stages of maturity. It is important that any agreement be structured so that it does not hinder other aspects of the development process. It may be sufficient for early-stage companies to put a smaller set of regulatory requirements in manufacturing, quality or clinical agreements [ 1 , 3 , 8 , 9 , 26 ]. These regulatory requirements may be relevant to material sourcing and supply, authoring, review, and provision of quality documents needed for registration dossiers, or notification of regulatory personnel of audit findings or changes affecting the regulatory status of the facility [ 18 , 27 , 28 , 29 , 30 ]. Master service agreements may also be a useful vehicle into which regulatory language can be added when one company carries the primary responsibility for most elements of the regulatory submissions and interactions.

Amongst the companies with regulatory agreements, approaches often appeared immature. The fact that most companies had no SOP in place for writing regulatory agreements may suggest that such agreements are not developed and managed consistently. Regulatory agreements might be used more often and more effectively if companies had better resources to guide their development. Although many respondents identified regulatory agency documents as potentially important sources of guidance, nearly one-quarter found that guidance on this topic was not helpful. Further, the usual sources of education on which regulatory professionals rely- trade meetings, government presentations, or consultants- fell short of their expectations. These results may point to ways in which governmental or professional organizations could help, by educating their membership about the use and value of such agreements. Further, companies could be helped if they had templates such as those already published for other types of vendor and partnership agreements [ 18 , 28 , 29 , 31 , 32 , 33 ]. An internet search to find “templates for pharmaceutical regulatory agreements”, conducted April 11, 2023, produced no references to such documents. For this reason, we have attempted to provide a comprehensive checklist of items (Table  5 ) that might be used as a starting point for agreements that involve shared responsibilities for regulatory submissions. This basic framework can of course be adjusted as needed by the addition or deletion of elements to address unanticipated activities.

A key aspect of implementation is having sufficient resources and support [ 34 ], including the participation and support of internal stakeholders [ 35 , 36 ]. Not surprisingly, some respondents were concerned that senior management and other relevant business functions were not engaged or supportive. Further, teams constructing regulatory agreements often failed to include members from relevant functions such as general administration and legal departments, commercial affairs, finance, business development and alliance management. The value of having a broadly based team has been emphasized for other types of agreements and might improve the acceptance of regulatory agreements at senior management levels. However, an unfocussed or untrained team could potentially impede the development of the agreement [ 37 ], so agreements would be easier to put into place if trained personnel could be dedicated to the construction of the regulatory agreement.

Survey validity in this study has depended on our ability to sample the target population appropriately. Survey participants were solicited widely from a specialized group of pharmaceutical and biotechnology professionals, mostly at the director level or above. This gave a lower response rate but also more freedom from bias than would be expected if the participants were invited only from known colleagues or contacts [ 38 ]. The response rate of 20% reported here is consistent with response rates seen in several recent studies conducted with busy executive respondents whose emails are often screened by company internet filters or administrative assistants [ 39 , 40 , 41 ]. Further, surveys with even a 10% response rate may be valid if those respondents are appropriate and able to provide rich data based on their knowledge [ 42 ]. Executives may also be wary of surveys because they fear that they will be asked to share company proprietary or protected information. Nonetheless, once the survey was started, professionals appeared to be strongly engaged, as reflected by their voluminous comments and completion rate of 83%.

Regulatory agreements appear to be evolving in the same way as precedent agreements in manufacturing, quality, and clinical trials, but are used currently by only a subset of companies. They are not required in the US, have no current agency or industry templates and little agency guidance. The choice to use them appears instead to depend on the complexity of the relationship, the extent of management and cross-functional team support and the specific needs of the project. In place of standalone agreements, other companies have chosen to include regulatory elements in other types of existing agreements. These can be sufficient when contractual relationships are simpler but can leave out important issues that need to be defined when participating in complex and at times multi-partnered joint ventures. Regulatory agreements would seem to be judicious, then, for relationships in which the complicated regulatory activities must be shared between the partners. Whether and how to implement such agreements would seem easier to decide if companies had better tools and templates to develop such agreements. A framework based on the feedback of industry respondents was developed here to aid in this effort.

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Wilhelm, M.E., Pire-Smerkanich, N. & Richmond, F.J. Standalone Regulatory Agreements for Product-Development Collaborations in the Medical Products Industry. Ther Innov Regul Sci (2024). https://doi.org/10.1007/s43441-024-00646-1

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Received : 22 July 2023

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DOI : https://doi.org/10.1007/s43441-024-00646-1

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