how to write questionnaire for research

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How to Develop a Questionnaire for Research

Last Updated: December 4, 2022 Fact Checked

This article was co-authored by Alexander Ruiz, M.Ed. . Alexander Ruiz is an Educational Consultant and the Educational Director of Link Educational Institute, a tutoring business based in Claremont, California that provides customizable educational plans, subject and test prep tutoring, and college application consulting. With over a decade and a half of experience in the education industry, Alexander coaches students to increase their self-awareness and emotional intelligence while achieving skills and the goal of achieving skills and higher education. He holds a BA in Psychology from Florida International University and an MA in Education from Georgia Southern University. There are 13 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 587,831 times.

A questionnaire is a technique for collecting data in which a respondent provides answers to a series of questions. [1] X Research source To develop a questionnaire that will collect the data you want takes effort and time. However, by taking a step-by-step approach to questionnaire development, you can come up with an effective means to collect data that will answer your unique research question.

Designing Your Questionnaire

• Come up with a research question. It can be one question or several, but this should be the focal point of your questionnaire.
• Develop one or several hypotheses that you want to test. The questions that you include on your questionnaire should be aimed at systematically testing these hypotheses.

• Dichotomous question: this is a question that will generally be a “yes/no” question, but may also be an “agree/disagree” question. It is the quickest and simplest question to analyze, but is not a highly sensitive measure.
• Open-ended questions: these questions allow the respondent to respond in their own words. They can be useful for gaining insight into the feelings of the respondent, but can be a challenge when it comes to analysis of data. It is recommended to use open-ended questions to address the issue of “why.” [2] X Research source
• Multiple choice questions: these questions consist of three or more mutually-exclusive categories and ask for a single answer or several answers. [3] X Research source Multiple choice questions allow for easy analysis of results, but may not give the respondent the answer they want.
• Rank-order (or ordinal) scale questions: this type of question asks your respondent to rank items or choose items in a particular order from a set. For example, it might ask your respondents to order five things from least to most important. These types of questions forces discrimination among alternatives, but does not address the issue of why the respondent made these discriminations. [4] X Research source
• Rating scale questions: these questions allow the respondent to assess a particular issue based on a given dimension. You can provide a scale that gives an equal number of positive and negative choices, for example, ranging from “strongly agree” to “strongly disagree.” [5] X Research source These questions are very flexible, but also do not answer the question “why.”

• Write questions that are succinct and simple. You should not be writing complex statements or using technical jargon, as it will only confuse your respondents and lead to incorrect responses.
• Ask only one question at a time. This will help avoid confusion
• Asking questions such as these usually require you to anonymize or encrypt the demographic data you collect.
• Determine if you will include an answer such as “I don’t know” or “Not applicable to me.” While these can give your respondents a way of not answering certain questions, providing these options can also lead to missing data, which can be problematic during data analysis.
• Put the most important questions at the beginning of your questionnaire. [7] X Research source This can help you gather important data even if you sense that your respondents may be becoming distracted by the end of the questionnaire.

• Only include questions that are directly useful to your research question. [9] X Trustworthy Source Food and Agricultural Organization of the United Nations Specialized agency of the United Nations responsible for leading international efforts to end world hunger and improve nutrition Go to source A questionnaire is not an opportunity to collect all kinds of information about your respondents.
• Avoid asking redundant questions. This will frustrate those who are taking your questionnaire.

• Consider if you want your questionnaire to collect information from both men and women. Some studies will only survey one sex.
• Consider including a range of ages in your target demographic. For example, you can consider young adult to be 18-29 years old, adults to be 30-54 years old, and mature adults to be 55+. Providing the an age range will help you get more respondents than limiting yourself to a specific age.
• Consider what else would make a person a target for your questionnaire. Do they need to drive a car? Do they need to have health insurance? Do they need to have a child under 3? Make sure you are very clear about this before you distribute your questionnaire.

• Consider an anonymous questionnaire. You may not want to ask for names on your questionnaire. This is one step you can take to prevent privacy, however it is often possible to figure out a respondent’s identity using other demographic information (such as age, physical features, or zipcode).
• Consider de-identifying the identity of your respondents. Give each questionnaire (and thus, each respondent) a unique number or word, and only refer to them using that new identifier. Shred any personal information that can be used to determine identity.
• Remember that you do not need to collect much demographic information to be able to identify someone. People may be wary to provide this information, so you may get more respondents by asking less demographic questions (if it is possible for your questionnaire).
• Make sure you destroy all identifying information after your study is complete.

Writing your questionnaire

• My name is Jack Smith and I am one of the creators of this questionnaire. I am part of the Department of Psychology at the University of Michigan, where I am focusing in developing cognition in infants.
• I’m Kelly Smith, a 3rd year undergraduate student at the University of New Mexico. This questionnaire is part of my final exam in statistics.
• My name is Steve Johnson, and I’m a marketing analyst for The Best Company. I’ve been working on questionnaire development to determine attitudes surrounding drug use in Canada for several years.

• I am collecting data regarding the attitudes surrounding gun control. This information is being collected for my Anthropology 101 class at the University of Maryland.
• This questionnaire will ask you 15 questions about your eating and exercise habits. We are attempting to make a correlation between healthy eating, frequency of exercise, and incidence of cancer in mature adults.
• This questionnaire will ask you about your recent experiences with international air travel. There will be three sections of questions that will ask you to recount your recent trips and your feelings surrounding these trips, as well as your travel plans for the future. We are looking to understand how a person’s feelings surrounding air travel impact their future plans.

• Beware that if you are collecting information for a university or for publication, you may need to check in with your institution’s Institutional Review Board (IRB) for permission before beginning. Most research universities have a dedicated IRB staff, and their information can usually be found on the school’s website.
• Remember that transparency is best. It is important to be honest about what will happen with the data you collect.
• Include an informed consent for if necessary. Note that you cannot guarantee confidentiality, but you will make all reasonable attempts to ensure that you protect their information. [12] X Research source

• Time yourself taking the survey. Then consider that it will take some people longer than you, and some people less time than you.
• Provide a time range instead of a specific time. For example, it’s better to say that a survey will take between 15 and 30 minutes than to say it will take 15 minutes and have some respondents quit halfway through.
• Use this as a reason to keep your survey concise! You will feel much better asking people to take a 20 minute survey than you will asking them to take a 3 hour one.

• Incentives can attract the wrong kind of respondent. You don’t want to incorporate responses from people who rush through your questionnaire just to get the reward at the end. This is a danger of offering an incentive. [13] X Research source
• Incentives can encourage people to respond to your survey who might not have responded without a reward. This is a situation in which incentives can help you reach your target number of respondents. [14] X Research source
• Consider the strategy used by SurveyMonkey. Instead of directly paying respondents to take their surveys, they offer 50 cents to the charity of their choice when a respondent fills out a survey. They feel that this lessens the chances that a respondent will fill out a questionnaire out of pure self-interest. [15] X Research source
• Consider entering each respondent in to a drawing for a prize if they complete the questionnaire. You can offer a 25$ gift card to a restaurant, or a new iPod, or a ticket to a movie. This makes it less tempting just to respond to your questionnaire for the incentive alone, but still offers the chance of a pleasant reward.

• Always proof read. Check for spelling, grammar, and punctuation errors.
• Include a title. This is a good way for your respondents to understand the focus of the survey as quickly as possible.
• Thank your respondents. Thank them for taking the time and effort to complete your survey.

Distributing Your Questionnaire

• Was the questionnaire easy to understand? Were there any questions that confused you?
• Was the questionnaire easy to access? (Especially important if your questionnaire is online).
• Do you feel the questionnaire was worth your time?
• Were you comfortable answering the questions asked?
• Are there any improvements you would make to the questionnaire?

• Use an online site, such as SurveyMonkey.com. This site allows you to write your own questionnaire with their survey builder, and provides additional options such as the option to buy a target audience and use their analytics to analyze your data. [19] X Research source
• Consider using the mail. If you mail your survey, always make sure you include a self-addressed stamped envelope so that the respondent can easily mail their responses back. Make sure that your questionnaire will fit inside a standard business envelope.
• Conduct face-to-face interviews. This can be a good way to ensure that you are reaching your target demographic and can reduce missing information in your questionnaires, as it is more difficult for a respondent to avoid answering a question when you ask it directly.
• Try using the telephone. While this can be a more time-effective way to collect your data, it can be difficult to get people to respond to telephone questionnaires.

• Make your deadline reasonable. Giving respondents up to 2 weeks to answer should be more than sufficient. Anything longer and you risk your respondents forgetting about your questionnaire.
• Consider providing a reminder. A week before the deadline is a good time to provide a gentle reminder about returning the questionnaire. Include a replacement of the questionnaire in case it has been misplaced by your respondent. [20] X Research source

Community Q&A

You Might Also Like

• ↑ https://www.questionpro.com/blog/what-is-a-questionnaire/
• ↑ https://www.hotjar.com/blog/open-ended-questions/
• ↑ https://www.questionpro.com/a/showArticle.do?articleID=survey-questions
• ↑ https://surveysparrow.com/blog/ranking-questions-examples/
• ↑ https://www.lumoa.me/blog/rating-scale/
• ↑ http://www.sciencebuddies.org/science-fair-projects/project_ideas/Soc_survey.shtml
• ↑ http://www.monash.edu.au/lls/hdr/design/2.4.3.html
• ↑ http://www.fao.org/docrep/W3241E/w3241e05.htm
• ↑ http://managementhelp.org/businessresearch/questionaires.htm
• ↑ https://www.surveymonkey.com/mp/survey-rewards/
• ↑ http://www.ideafit.com/fitness-library/how-to-develop-a-questionnaire
• ↑ https://www.surveymonkey.com/mp/take-a-tour/?ut_source=header

About This Article

To develop a questionnaire for research, identify the main objective of your research to act as the focal point for the questionnaire. Then, choose the type of questions that you want to include, and come up with succinct, straightforward questions to gather the information that you need to answer your questions. Keep your questionnaire as short as possible, and identify a target demographic who you would like to answer the questions. Remember to make the questionnaires as anonymous as possible to protect the integrity of the person answering the questions! For tips on writing out your questions and distributing the questionnaire, keep reading! Did this summary help you? Yes No

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Harvard University Program on Survey Research

• Questionnaire Design Tip Sheet

This PSR Tip Sheet provides some basic tips about how to write good survey questions and design a good survey questionnaire.

PSR Resources

• Managing and Manipulating Survey Data: A Beginners Guide
• Finding and Hiring Survey Contractors
• How to Frame and Explain the Survey Data Used in a Thesis
• Overview of Cognitive Testing and Questionnaire Evaluation
• Sampling, Coverage, and Nonresponse Tip Sheet
• Introduction to Surveys for Honors Thesis Writers
• PSR Introduction to the Survey Process
• Related Centers/Programs at Harvard
• General Survey Reference
• Institutional Review Boards
• Select Funding Opportunities
• Survey Analysis Software
• Professional Standards
• Professional Organizations
• Major Public Polls
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• Major Longitudinal Surveys
• Other Links

How to Design Effective Research Questionnaires for Robust Findings

As a staple in data collection, questionnaires help uncover robust and reliable findings that can transform industries, shape policies, and revolutionize understanding. Whether you are exploring societal trends or delving into scientific phenomena, the effectiveness of your research questionnaire can make or break your findings.

In this article, we aim to understand the core purpose of questionnaires, exploring how they serve as essential tools for gathering systematic data, both qualitative and quantitative, from diverse respondents. Read on as we explore the key elements that make up a winning questionnaire, the art of framing questions which are both compelling and rigorous, and the careful balance between simplicity and depth.

Table of Contents

The Role of Questionnaires in Research

So, what is a questionnaire? A questionnaire is a structured set of questions designed to collect information, opinions, attitudes, or behaviors from respondents. It is one of the most commonly used data collection methods in research. Moreover, questionnaires can be used in various research fields, including social sciences, market research, healthcare, education, and psychology. Their adaptability makes them suitable for investigating diverse research questions.

Questionnaire and survey  are two terms often used interchangeably, but they have distinct meanings in the context of research. A survey refers to the broader process of data collection that may involve various methods. A survey can encompass different data collection techniques, such as interviews , focus groups, observations, and yes, questionnaires.

Pros and Cons of Using Questionnaires in Research:

While questionnaires offer numerous advantages in research, they also come with some disadvantages that researchers must be aware of and address appropriately. Careful questionnaire design, validation, and consideration of potential biases can help mitigate these disadvantages and enhance the effectiveness of using questionnaires as a data collection method.

Structured vs Unstructured Questionnaires

Structured questionnaire:.

A structured questionnaire consists of questions with predefined response options. Respondents are presented with a fixed set of choices and are required to select from those options. The questions in a structured questionnaire are designed to elicit specific and quantifiable responses. Structured questionnaires are particularly useful for collecting quantitative data and are often employed in surveys and studies where standardized and comparable data are necessary.

Advantages of Structured Questionnaires:

• Easy to analyze and interpret: The fixed response options facilitate straightforward data analysis and comparison across respondents.
• Efficient for large-scale data collection: Structured questionnaires are time-efficient, allowing researchers to collect data from a large number of respondents.
• Reduces response bias: The predefined response options minimize potential response bias and maintain consistency in data collection.

Limitations of Structured Questionnaires:

• Lack of depth: Structured questionnaires may not capture in-depth insights or nuances as respondents are limited to pre-defined response choices. Hence, they may not reveal the reasons behind respondents’ choices, limiting the understanding of their perspectives.
• Limited flexibility: The fixed response options may not cover all potential responses, therefore, potentially restricting respondents’ answers.

Unstructured Questionnaire:

An unstructured questionnaire consists of questions that allow respondents to provide detailed and unrestricted responses. Unlike structured questionnaires, there are no predefined response options, giving respondents the freedom to express their thoughts in their own words. Furthermore, unstructured questionnaires are valuable for collecting qualitative data and obtaining in-depth insights into respondents’ experiences, opinions, or feelings.

Advantages of Unstructured Questionnaires:

• Rich qualitative data: Unstructured questionnaires yield detailed and comprehensive qualitative data, providing valuable and novel insights into respondents’ perspectives.
• Flexibility in responses: Respondents have the freedom to express themselves in their own words. Hence, allowing for a wide range of responses.

Limitations of Unstructured Questionnaires:

• Time-consuming analysis: Analyzing open-ended responses can be time-consuming, since, each response requires careful reading and interpretation.
• Subjectivity in interpretation: The analysis of open-ended responses may be subjective, as researchers interpret and categorize responses based on their judgment.
• May require smaller sample size: Due to the depth of responses, researchers may need a smaller sample size for comprehensive analysis, making generalizations more challenging.

Types of Questions in a Questionnaire

In a questionnaire, researchers typically use the following most common types of questions to gather a variety of information from respondents:

1. Open-Ended Questions:

These questions allow respondents to provide detailed and unrestricted responses in their own words. Open-ended questions are valuable for gathering qualitative data and in-depth insights.

Example: What suggestions do you have for improving our product?

2. Multiple-Choice Questions

Respondents choose one answer from a list of provided options. This type of question is suitable for gathering categorical data or preferences.

Example: Which of the following social media/academic networking platforms do you use to promote your research?

• ResearchGate
• Academia.edu

3. Dichotomous Questions

Respondents choose between two options, typically “yes” or “no”, “true” or “false”, or “agree” or “disagree”.

Example: Have you ever published in open access journals before?

4. Scaling Questions

These questions, also known as rating scale questions, use a predefined scale that allows respondents to rate or rank their level of agreement, satisfaction, importance, or other subjective assessments. These scales help researchers quantify subjective data and make comparisons across respondents.

There are several types of scaling techniques used in scaling questions:

i. Likert Scale:

The Likert scale is one of the most common scaling techniques. It presents respondents with a series of statements and asks them to rate their level of agreement or disagreement using a range of options, typically from “strongly agree” to “strongly disagree”.For example: Please indicate your level of agreement with the statement: “The content presented in the webinar was relevant and aligned with the advertised topic.”

• Strongly Agree
• Strongly Disagree

ii. Semantic Differential Scale:

The semantic differential scale measures respondents’ perceptions or attitudes towards an item using opposite adjectives or bipolar words. Respondents rate the item on a scale between the two opposites. For example:

• Easy —— Difficult
• Satisfied —— Unsatisfied
• Very likely —— Very unlikely

iii. Numerical Rating Scale:

This scale requires respondents to provide a numerical rating on a predefined scale. It can be a simple 1 to 5 or 1 to 10 scale, where higher numbers indicate higher agreement, satisfaction, or importance.

iv. Ranking Questions:

Respondents rank items in order of preference or importance. Ranking questions help identify preferences or priorities.

Example: Please rank the following features of our app in order of importance (1 = Most Important, 5 = Least Important):

• User Interface
• Functionality
• Customer Support

By using a mix of question types, researchers can gather both quantitative and qualitative data, providing a comprehensive understanding of the research topic and enabling meaningful analysis and interpretation of the results. The choice of question types depends on the research objectives , the desired depth of information, and the data analysis requirements.

Methods of Administering Questionnaires

There are several methods for administering questionnaires, and the choice of method depends on factors such as the target population, research objectives , convenience, and resources available. Here are some common methods of administering questionnaires:

Each method has its advantages and limitations. Online surveys offer convenience and a large reach, but they may be limited to individuals with internet access. Face-to-face interviews allow for in-depth responses but can be time-consuming and costly. Telephone surveys have broad reach but may be limited by declining response rates. Researchers should choose the method that best suits their research objectives, target population, and available resources to ensure successful data collection.

How to Design a Questionnaire

Designing a good questionnaire is crucial for gathering accurate and meaningful data that aligns with your research objectives. Here are essential steps and tips to create a well-designed questionnaire:

1. Define Your Research Objectives : Clearly outline the purpose and specific information you aim to gather through the questionnaire.

2. Identify Your Target Audience : Understand respondents’ characteristics and tailor the questionnaire accordingly.

3. Develop the Questions :

• Write Clear and Concise Questions
• Avoid Leading or Biasing Questions
• Sequence Questions Logically
• Group Related Questions
• Include Demographic Questions

4. Provide Well-defined Response Options : Offer exhaustive response choices for closed-ended questions.

5. Consider Skip Logic and Branching : Customize the questionnaire based on previous answers.

6. Pilot Test the Questionnaire : Identify and address issues through a pilot study .

7. Seek Expert Feedback : Validate the questionnaire with subject matter experts.

8. Obtain Ethical Approval : Comply with ethical guidelines , obtain consent, and ensure confidentiality before administering the questionnaire.

9. Administer the Questionnaire : Choose the right mode and provide clear instructions.

10. Test the Survey Platform : Ensure compatibility and usability for online surveys.

By following these steps and paying attention to questionnaire design principles, you can create a well-structured and effective questionnaire that gathers reliable data and helps you achieve your research objectives.

Characteristics of a Good Questionnaire

A good questionnaire possesses several essential elements that contribute to its effectiveness. Furthermore, these characteristics ensure that the questionnaire is well-designed, easy to understand, and capable of providing valuable insights. Here are some key characteristics of a good questionnaire:

1. Clarity and Simplicity : Questions should be clear, concise, and unambiguous. Avoid using complex language or technical terms that may confuse respondents. Simple and straightforward questions ensure that respondents interpret them consistently.

2. Relevance and Focus : Each question should directly relate to the research objectives and contribute to answering the research questions. Consequently, avoid including extraneous or irrelevant questions that could lead to data clutter.

3. Mix of Question Types : Utilize a mix of question types, including open-ended, Likert scale, and multiple-choice questions. This variety allows for both qualitative and quantitative data collections .

4. Validity and Reliability : Ensure the questionnaire measures what it intends to measure (validity) and produces consistent results upon repeated administration (reliability). Validation should be conducted through expert review and previous research.

5. Appropriate Length : Keep the questionnaire’s length appropriate and manageable to avoid respondent fatigue or dropouts. Long questionnaires may result in incomplete or rushed responses.

6. Clear Instructions : Include clear instructions at the beginning of the questionnaire to guide respondents on how to complete it. Explain any technical terms, formats, or concepts if necessary.

7. User-Friendly Format : Design the questionnaire to be visually appealing and user-friendly. Use consistent formatting, adequate spacing, and a logical page layout.

8. Data Validation and Cleaning : Incorporate validation checks to ensure data accuracy and reliability. Consider mechanisms to detect and correct inconsistent or missing responses during data cleaning.

By incorporating these characteristics, researchers can create a questionnaire that maximizes data quality, minimizes response bias, and provides valuable insights for their research.

In the pursuit of advancing research and gaining meaningful insights, investing time and effort into designing effective questionnaires is a crucial step. A well-designed questionnaire is more than a mere set of questions; it is a masterpiece of precision and ingenuity. Each question plays a vital role in shaping the narrative of our research, guiding us through the labyrinth of data to meaningful conclusions. Indeed, a well-designed questionnaire serves as a powerful tool for unlocking valuable insights and generating robust findings that impact society positively.

Have you ever designed a research questionnaire? Reflect on your experience and share your insights with researchers globally through Enago Academy’s Open Blogging Platform . Join our diverse community of 1000K+ researchers and authors to exchange ideas, strategies, and best practices, and together, let’s shape the future of data collection and maximize the impact of questionnaires in the ever-evolving landscape of research.

Frequently Asked Questions

A research questionnaire is a structured tool used to gather data from participants in a systematic manner. It consists of a series of carefully crafted questions designed to collect specific information related to a research study.

Questionnaires play a pivotal role in both quantitative and qualitative research, enabling researchers to collect insights, opinions, attitudes, or behaviors from respondents. This aids in hypothesis testing, understanding, and informed decision-making, ensuring consistency, efficiency, and facilitating comparisons.

Questionnaires are a versatile tool employed in various research designs to gather data efficiently and comprehensively. They find extensive use in both quantitative and qualitative research methodologies, making them a fundamental component of research across disciplines. Some research designs that commonly utilize questionnaires include: a) Cross-Sectional Studies b) Longitudinal Studies c) Descriptive Research d) Correlational Studies e) Causal-Comparative Studies f) Experimental Research g) Survey Research h) Case Studies i) Exploratory Research

A survey is a comprehensive data collection method that can include various techniques like interviews and observations. A questionnaire is a specific set of structured questions within a survey designed to gather standardized responses. While a survey is a broader approach, a questionnaire is a focused tool for collecting specific data.

The choice of questionnaire type depends on the research objectives, the type of data required, and the preferences of respondents. Some common types include: • Structured Questionnaires: These questionnaires consist of predefined, closed-ended questions with fixed response options. They are easy to analyze and suitable for quantitative research. • Semi-Structured Questionnaires: These questionnaires combine closed-ended questions with open-ended ones. They offer more flexibility for respondents to provide detailed explanations. • Unstructured Questionnaires: These questionnaires contain open-ended questions only, allowing respondents to express their thoughts and opinions freely. They are commonly used in qualitative research.

Following these steps ensures effective questionnaire administration for reliable data collection: • Choose a Method: Decide on online, face-to-face, mail, or phone administration. • Online Surveys: Use platforms like SurveyMonkey • Pilot Test: Test on a small group before full deployment • Clear Instructions: Provide concise guidelines • Follow-Up: Send reminders if needed

Thank you, Riya. This is quite helpful. As discussed, response bias is one of the disadvantages in the use of questionnaires. One way to help limit this can be to use scenario based questions. These type of questions may help the respondents to be more reflective and active in the process.

Thank you, Dear Riya. This is quite helpful.

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Great survey questions: How to write them & avoid common mistakes

Learning how to write survey questions is both art and science. The wording you choose can make the difference between accurate, useful data and just the opposite. Fortunately, we’ve got a raft of tips to help.

Figuring out how to make a good survey that yields actionable insights is all about sweating the details. And writing effective questionnaire questions is the first step.

Essential for success is understanding the different types of survey questions and how they work. Each format needs a slightly different approach to question-writing.

In this article, we’ll share how to write survey questionnaires and list some common errors to avoid so you can improve your surveys and the data they provide.

Free eBook: The Qualtrics survey template guide

Survey question types

Did you know that Qualtrics provides 23 question types you can use in your surveys ? Some are very popular and used frequently by a wide range of people from students to market researchers, while others are more specialist and used to explore complex topics. Here’s an introduction to some basic survey question formats, and how to write them well.

Multiple choice

Familiar to many, multiple choice questions ask a respondent to pick from a range of options. You can set up the question so that only one selection is possible, or allow more than one to be ticked.

When writing a multiple choice question…

• Be clear about whether the survey taker should choose one (“pick only one”) or several (“select all that apply”).
• Think carefully about the options you provide, since these will shape your results data.
• The phrase “of the following” can be helpful for setting expectations. For example, if you ask “What is your favorite meal” and provide the options “hamburger and fries”, “spaghetti and meatballs”, there’s a good chance your respondent’s true favorite won’t be included. If you add “of the following” the question makes more sense.

Asking participants to rank things in order, whether it’s order of preference, frequency or perceived value, is done using a rank structure. There can be a variety of interfaces, including drag-and-drop, radio buttons, text boxes and more.

When writing a rank order question…

• Explain how the interface works and what the respondent should do to indicate their choice. For example “drag and drop the items in this list to show your order of preference.”
• Be clear about which end of the scale is which. For example, “With the best at the top, rank these items from best to worst”
• Be as specific as you can about how the respondent should consider the options and how to rank them. For example, “thinking about the last 3 months’ viewing, rank these TV streaming services in order of quality, starting with the best”

Slider structures ask the respondent to move a pointer or button along a scale, usually a numerical one, to indicate their answers.

When writing a slider question…

• Consider whether the question format will be intuitive to your respondents, and whether you should add help text such as “click/tap and drag on the bar to select your answer”
• Qualtrics includes the option for an open field where your respondent can type their answer instead of using a slider. If you offer this, make sure to reference it in the survey question so the respondent understands its purpose.

Also known as an open field question, this format allows survey-takers to answer in their own words by typing into the comments box.

When writing a text entry question…

• Use open-ended question structures like “How do you feel about…” “If you said x, why?” or “What makes a good x?”
• Open-ended questions take more effort to answer, so use these types of questions sparingly.
• Be as clear and specific as possible in how you frame the question. Give them as much context as you can to help make answering easier. For example, rather than “How is our customer service?”, write “Thinking about your experience with us today, in what areas could we do better?”

Matrix table

Matrix structures allow you to address several topics using the same rating system, for example a Likert scale (Very satisfied / satisfied / neither satisfied nor dissatisfied / dissatisfied / very dissatisfied).

When writing a matrix table question…

• Make sure the topics are clearly differentiated from each other, so that participants don’t get confused by similar questions placed side by side and answer the wrong one.
• Keep text brief and focused. A matrix includes a lot of information already, so make it easier for your survey-taker by using plain language and short, clear phrases in your matrix text.
• Add detail to the introductory static text if necessary to help keep the labels short. For example, if your introductory text says “In the Philadelphia store, how satisfied were you with the…” you can make the topic labels very brief, for example “staff friendliness” “signage” “price labeling” etc.

Now that you know your rating scales from your open fields, here are the 7 most common mistakes to avoid when you write questions. We’ve also added plenty of survey question examples to help illustrate the points.

Likert Scale Questions

Likert scales are commonly used in market research when dealing with single topic survyes. They're simple and most reliable when combatting survey bias . For each question or statement, subjects choose from a range of possible responses. The responses, for example, typically include:

• Strongly agree
• Strongly disagree

7 survey question examples to avoid.

There are countless great examples of writing survey questions but how do you know if your types of survey questions will perform well? We've highlighted the 7 most common mistakes when attempting to get customer feedback with online surveys.

Survey question mistake #1: Failing to avoid leading words / questions

Subtle wording differences can produce great differences in results. For example, non-specific words and ideas can cause a certain level of confusing ambiguity in your survey. “Could,” “should,” and “might” all sound about the same, but may produce a 20% difference in agreement to a question.

In addition, strong words such as “force” and “prohibit” represent control or action and can bias your results.

Example: The government should force you to pay higher taxes.

No one likes to be forced, and no one likes higher taxes. This agreement scale question makes it sound doubly bad to raise taxes. When survey questions read more like normative statements than questions looking for objective feedback, any ability to measure that feedback becomes difficult.

Wording alternatives can be developed. How about simple statements such as: The government should increase taxes, or the government needs to increase taxes.

Example: How would you rate the career of legendary outfielder Joe Dimaggio?

This survey question tells you Joe Dimaggio is a legendary outfielder. This type of wording can bias respondents.

How about replacing the word “legendary” with “baseball” as in: How would you rate the career of baseball outfielder Joe Dimaggio? A rating scale question like this gets more accurate answers from the start.

Survey question mistake #2: Failing to give mutually exclusive choices

Multiple choice response options should be mutually exclusive so that respondents can make clear choices. Don’t create ambiguity for respondents.

Review your survey and identify ways respondents could get stuck with either too many or no single, correct answers to choose from.

Example: What is your age group?

What answer would you select if you were 10, 20, or 30? Survey questions like this will frustrate a respondent and invalidate your results.

Example: What type of vehicle do you own?

This question has the same problem. What if the respondent owns a truck, hybrid, convertible, cross-over, motorcycle, or no vehicle at all?

Survey question mistake #3: Not asking direct questions

Questions that are vague and do not communicate your intent can limit the usefulness of your results. Make sure respondents know what you’re asking.

Example: What suggestions do you have for improving Tom’s Tomato Juice?

This question may be intended to obtain suggestions about improving taste, but respondents will offer suggestions about texture, the type of can or bottle, about mixing juices, or even suggestions relating to using tomato juice as a mixer or in recipes.

Example: What do you like to do for fun?

Finding out that respondents like to play Scrabble isn’t what the researcher is looking for, but it may be the response received. It is unclear that the researcher is asking about movies vs. other forms of paid entertainment. A respondent could take this question in many directions.

Survey question mistake #4: Forgetting to add a “prefer not to answer” option

Sometimes respondents may not want you to collect certain types of information or may not want to provide you with the types of information requested.

Questions about income, occupation, personal health, finances, family life, personal hygiene, and personal, political, or religious beliefs can be too intrusive and be rejected by the respondent.

Privacy is an important issue to most people. Incentives and assurances of confidentiality can make it easier to obtain private information.

While current research does not support that PNA (Prefer Not to Answer) options increase data quality or response rates, many respondents appreciate this non-disclosure option.

Furthermore, different cultural groups may respond differently. One recent study found that while U.S. respondents skip sensitive questions, Asian respondents often discontinue the survey entirely.

• What is your race?
• What is your age?
• Did you vote in the last election?
• What are your religious beliefs?
• What are your political beliefs?
• What is your annual household income?

These types of questions should be asked only when absolutely necessary. In addition, they should always include an option to not answer. (e.g. “Prefer Not to Answer”).

Survey question mistake #5: Failing to cover all possible answer choices

Do you have all of the options covered? If you are unsure, conduct a pretest version of your survey using “Other (please specify)” as an option.

If more than 10% of respondents (in a pretest or otherwise) select “other,” you are probably missing an answer. Review the “Other” text your test respondents have provided and add the most frequently mentioned new options to the list.

Example: You indicated that you eat at Joe's fast food once every 3 months. Why don't you eat at Joe's more often?

There isn't a location near my house

I don't like the taste of the food

Never heard of it

This question doesn’t include other options, such as healthiness of the food, price/value or some “other” reason. Over 10% of respondents would probably have a problem answering this question.

Survey question mistake #6: Not using unbalanced scales carefully

Unbalanced scales may be appropriate for some situations and promote bias in others.

For instance, a hospital might use an Excellent - Very Good - Good - Fair scale where “Fair” is the lowest customer satisfaction point because they believe “Fair” is absolutely unacceptable and requires correction.

The key is to correctly interpret your analysis of the scale. If “Fair” is the lowest point on a scale, then a result slightly better than fair is probably not a good one.

Additionally, scale points should represent equi-distant points on a scale. That is, they should have the same equal conceptual distance from one point to the next.

For example, researchers have shown the points to be nearly equi-distant on the strongly disagree–disagree–neutral–agree–strongly agree scale.

Set your bottom point as the worst possible situation and top point as the best possible, then evenly spread the labels for your scale points in-between.

Example: What is your opinion of Crazy Justin's auto-repair?

Pretty good

The Best Ever

This question puts the center of the scale at fantastic, and the lowest possible rating as “Pretty Good.” This question is not capable of collecting true opinions of respondents.

Survey question mistake #7: Not asking only one question at a time

There is often a temptation to ask multiple questions at once. This can cause problems for respondents and influence their responses.

Review each question and make sure it asks only one clear question.

Example: What is the fastest and most economical internet service for you?

This is really asking two questions. The fastest is often not the most economical.

Example: How likely are you to go out for dinner and a movie this weekend?

Dinner and Movie

Dinner Only

Even though “dinner and a movie” is a common term, this is two questions as well. It is best to separate activities into different questions or give respondents these options:

5 more tips on how to write a survey

Here are 5 easy ways to help ensure your survey results are unbiased and actionable.

1. Use the Funnel Technique

Structure your questionnaire using the “funnel” technique. Start with broad, general interest questions that are easy for the respondent to answer. These questions serve to warm up the respondent and get them involved in the survey before giving them a challenge. The most difficult questions are placed in the middle – those that take time to think about and those that are of less general interest. At the end, we again place general questions that are easier to answer and of broad interest and application. Typically, these last questions include demographic and other classification questions.

2. Use “Ringer” questions

In social settings, are you more introverted or more extroverted?

That was a ringer question and its purpose was to recapture your attention if you happened to lose focus earlier in this article.

Questionnaires often include “ringer” or “throw away” questions to increase interest and willingness to respond to a survey. These questions are about hot topics of the day and often have little to do with the survey. While these questions will definitely spice up a boring survey, they require valuable space that could be devoted to the main topic of interest. Use this type of question sparingly.

3. Keep your questionnaire short

Questionnaires should be kept short and to the point. Most long surveys are not completed, and the ones that are completed are often answered hastily. A quick look at a survey containing page after page of boring questions produces a response of, “there is no way I’m going to complete this thing”. If a questionnaire is long, the person must either be very interested in the topic, an employee, or paid for their time. Web surveys have some advantages because the respondent often can't view all of the survey questions at once. However, if your survey's navigation sends them page after page of questions, your response rate will drop off dramatically.

How long is too long?  The sweet spot is to keep the survey to less than five minutes. This translates into about 15 questions. The average respondent is able to complete about 3 multiple choice questions per minute. An open-ended text response question counts for about three multiple choice questions depending, of course, on the difficulty of the question. While only a rule of thumb, this formula will accurately predict the limits of your survey.

4. Watch your writing style

The best survey questions are always easy to read and understand. As a rule of thumb, the level of sophistication in your survey writing should be at the 9th to 11th grade level. Don’t use big words. Use simple sentences and simple choices for the answers. Simplicity is always best.

5. Use randomization

We know that being the first on the list in elections increases the chance of being elected. Similar bias occurs in all questionnaires when the same answer appears at the top of the list for each respondent. Randomization corrects this bias by randomly rotating the order of the multiple choice matrix questions for each respondent.

Free Templates: Get free access to 30+ of Qualtrics' best survey templates

While not totally inclusive, these seven survey question tips are common offenders in building good survey questions. And the five tips above should steer you in the right direction.

Focus on creating clear questions and having an understandable, appropriate, and complete set of answer choices. Great questions and great answer choices lead to great research success. To learn more about survey question design, download our eBook, The Qualtrics survey template guide or get started with a free survey account with our world-class survey software .

Sarah Fisher

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Creating a Questionnaire

Create the perfect questionnaire and collect actionable data using our online guide!

Table of Contents

• How to Create

Questionnaire Types

• Collecting Responses
• Analyzing Results
• Getting Started

What is a Questionnaire?

Definition: A questionnaire is a convenient way to collect feedback. A questionnaire can be used to measure customer satisfaction, capture employee feedback, or even conduct product research. Responses can be collected via email, web link, QR code, or using a survey panel.

The term "survey" and "questionnaire" are commonly used interchangeably. A questionnaire refers to the questions used to collect feedback (the form itself). A survey relates to the entire research process, including summarizing and analyzing questionnaire data.

Getting Started + Tips

How to make a questionnaire: Keep questions short and focused on one topic at a time. Use multiple-choice questions to fit answers into a specific category. Use an open-ended question to capture comments. A Likert scale or MaxDiff question can be used for market research. Collect responses for your questionnaire using an email collector, an anonymous link, or even a QR code.

The following 6 tips will help you create the perfect questionnaire:

1) Use 10 Questions or Less

The shorter you keep your survey, the higher your completion rates. Longer questionnaires usually tend to have a high drop-off percentage. Keeping your surveys to 10 questions or fewer forces you to draft a study that only includes important questions; you should remove trivial questions during the draft process.

2) One Idea Per Question

Make sure each question only covers one topic. Try to include only one topic at a time. For example, in an employee survey, you would not want to ask, "Do you feel satisfied with your compensation and career advancement?". Instead, you would like to separate "compensation" and "career advancement" into two questions or use a Likert scale , putting each question on a separate row.

3) Group Similar Questions Together

Suppose the survey is more than ten questions; similar questions should be grouped on separate pages. If you don't want to use more than one page, add extra spacing between groups of the question; extra white space can increase the increase the readability of your questionnaire.

4) Use Skip/Display Logic

If you have questions that only apply to certain people, consider using skip or display logic to show those questions conditionally. This will help reduce the length of your survey and boost response rates.

If you have questions that only apply to certain people, consider using skip or display logic to show those questions conditionally. This will help reduce the length of your survey and boost response rates. For example, if you asked, "Are you currently looking for new employment opportunities?". If the answer were "yes," a follow-up question would ask, "Why?"

5) Use Research Questions Like MaxDiff

Research questions are an excellent tool for customer or product questionnaires. Instead of asking multiple questions on which features are essential or what price is desirable, question types like MaxDiff and Conjoint will provide you with high-quality, actionable data that can be used for feature prioritization and product pricing. In addition, these question types will reduce the length of your questionnaire.

6) Keep the Audience in Mind

An employee questionnaire should use an anonymous link to collect responses; this will help boost trust and increase honest answers. If doing a customer study, consider adding custom data to the weblink to help identify responses. A survey panel and current customers can lend fresh perspectives for general market research.

Questionnaire Templates

Adding customer surveys to your Google review strategy will add additional data points to improve customer satisfaction. In addition, surveys are a valuable tool to identify ways to improve, establish internal benchmarks, and conduct pricing and product research to improve your company's products.

While there are numerous types of questionnaires (or survey types), these are the five most common general categories:

1) Customer Satisfaction

Capturing customer feedback is one of the most common uses of questionnaires. A good customer satisfaction survey will always revolve around a Net Promoter Score question. When the Net Promoter Score question results are tallied, one number from -100 is 100 is displayed. This number is ideal for benchmarks. Net Promoter provides quick and actionable feedback when combined with an open-ended text question.

2) Customer Effort

Measuring how easily customers can complete a purchase or take a specific action is crucial for the customer experience strategy. A customer effort score question is a rating scale from 1 to 7 (disagree to agree). Results for this question are averaged; the higher the score, the easier it is for your customers to complete tasks.

3) Employee Satisfaction & Engagement

Employee satisfaction and engagement are often used interchangeably but measure different things. Both types of surveys often use opinion scales to ask questions.

Employee satisfaction measures how satisfied employees are with their job and work environment. Standard measures of employee satisfaction include salary, benefits, and co-worker relationships.

Employee engagement relates to the emotional commitment employees have to an organization. It goes beyond simple satisfaction. Standard measures of engagement include belief in the company mission, opportunities for career growth, and being inspired to perform at a high level.

4) Employee Exit Interviews

When employees leave for new opportunities, sending a questionnaire is a great way to understand why that employee is leaving. The feedback obtained here can be used to improve the workplace and reduce employee turnover.

5) Product Research

MaxDiff is used to identify what is most important to your audience. For example, if building a new mobile application, asking a group of users what they think is least and most important will help guide product strategy; your team should only focus on the important areas.

For pricing a new product, Van Westendorp will give you a range of prices the market is willing to expect. You could price your product too high or too low without a question like this, reducing your market penetration.

Collecting Responses For Your Questionnaire

There are a few different ways to collect feedback for questionnaires. Depending on your needs, each one could have an advantage.

With email distribution, you would upload a list of email addresses, and the platform would automatically place a link to your questionnaire inside the email body. One advantage is sending email reminders to respondents who still need to complete your survey. In addition, the email links are unique for each respondent, so you can track email open and click rates. As a result, email surveys are ideal for customer research.

A web link is a convenient way to collect feedback at your convenience. You can place a web link on social media, your website, or even inside your CRM email program (instead of an email collector with a unique link to each person). Custom data can be included in the link, such as store location. This custom data can be used to segment and filter results.

Anonymous Link

When you want to protect your respondents' identities, you use an anonymous link . Anonymous inks do not store respondent information, IP address, or email address. Because of this, anonymous survey links are perfect for employee surveys.

QR code Surveys

QR code surveys can be placed on paper receipts, product packaging, or flyers. In addition, QR codes are a great way to collect feedback after or during an event or even during in-person focus groups.

Survey Panels

If you're conducting market research and need access to a customer base, using a survey panel will get you the responses required. A good survey panel will allow you to target specific demographics, job titles, or interest levels (such as car enthusiasts). When using survey panels, you'll want to double-check and clean your data for low-quality responses. People who speed through your survey or mark the first answer for all questions should be removed.

How to Analyze Questionnaire Data

When analyzing the data from a questionnaire, consider a few advanced techniques like the ones below. These techniques will give you better insights than just simple graphs and charts.

Creating a segment or a cross-tabulation is the easiest way to dive deeper into your results. For example, if you conducted an employee satisfaction survey, the overall scores for the company could be high. But that might only tell part of the story. For example, if your company has multiple departments, you should create a cross-tabulation for each department. You might notice that there is one department with low scores. or one department with high scores.

If your company conducted its first Net Promoter Score survey and the results were -10, that score would be your benchmark. Each subsequent customer survey you run should be compared against that initial number to improve it each time.

TURF Analysis

This is an advanced research technique but very valuable. TURF analysis analysis stands for "Total Unduplicated Reach and Frequency" and is used to find the combination of items that would provide the highest reach level. For example, suppose you ask, "Which of the following flavor of ice cream would you buy?" If you run a TURF analysis on the results, you could find the top 3 or 4 combinations of flavors that would result in the highest sales.

Unsure Where to Start?

Creating a questionnaire can be a challenging process. However, these three suggestions can help you with the perfect questionnaire strategy.

1) Talk With Your Team

Some departments might want to conduct pricing research and do simple Net Promoter Score surveys. Having your organization aligned on strategy will simplify the process and eliminate any possibility of re-work. An aligned strategy will also mean a shorter study with fewer overlapping questions.

2) Start with a Template

A pre-made template will show you how to format and word questions. Next, try multiple templates to understand the various question types.

3) Look at Competitor Surveys

You might notice competitors asking specific questions - this would be a sign that those questions provide valuable metrics. If you can incorporate the great things your competition does while making it more efficient for respondents, your questionnaire campaigns will have a greater chance of success.

Get Started Now

We have you covered on anything from customer surveys, employee surveys, to market research. Get started and create your first survey for free.

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How to write a survey questionnaire

The questionnaire is a researcher’s most important tool! You need to ask the right questions, in the right way to get the insight you need. This guide explains what makes a good survey, be it online or telephone, and what pitfalls to avoid.

Starting the questionnaire

Before starting to write your survey, you should revisit the original project objectives to keep your line of questioning on-track.

It’s a good idea to start with a ‘wish list’ – noting down all the questions that you and your stakeholders would like to include. It’s helpful to have everything in contention written down so you can prioritise which are the most important questions. It’s also helpful to start grouping these questions together by broad topic area to have an overview of what you’re covering and help get the order right.

Top tip: Once you have written the first draft of your questionnaire go through and note next to each question which objective it helps to answer. If a question doesn’t help answer any of the objectives – ditch it!

The key things to consider when structuring a questionnaire are:

• Introduction and screening:  In a few sentences, explain what the research is about, how you will use the answers and how long it will take to complete. Be honest, if you say it will take 5 minutes to complete but actually it’s going to take 10 minutes, people are likely to drop out halfway through.

You might also need to ask some screening questions which collect basic profiling characteristics to make sure you are talking to the right type or enough of a certain type of student (e.g. subject area or home / overseas) or business (e.g. location or sector).

• Create a natural flow:  It’s useful to think about the order in which people would normally talk about a topic. For example, if you are running a survey to measure student satisfaction during the pandemic, you might want to consider structuring your questionnaire chronologically, starting with arrival in Freshers’ Week through to current views on course delivery.

Linked to this, if you need to tackle harder or more sensitive topics, ‘warm up’ respondents by asking easier or more general questions first. Likewise, if you need to collect more personal information, then place these questions at the end, unless the information is needed to screen at the beginning of the survey. And remember to include a ‘Prefer not to say’ option.

• Vary question types:  Try and add different types of question to maintain interest, for example, when capturing how satisfied students are with various aspects of their learning experience, you could combine agree-disagree statements with questions that ask them to rank different elements of learning by level of satisfaction.

Top tip: Consider ‘routing’ respondents through the survey so that they are only asked questions that are relevant to them. For example, you’ve already established earlier in the survey whether or not a local employer is able to offer a work placement to your students. If they are, you’ll want to ask them a series of follow-up questions to collect more details. If they aren’t, then they should skip past these questions. Be aware not all survey platforms allow for routing, so if you can’t apply this, make sure you acknowledge this at the follow-up questions by including an appropriate response option like ‘Not applicable’.

Types of question.

How you ask your questions will determine the sort of data you collect and the type of analysis you can conduct. Think about how you will use your survey data at the end and what this means for how you ask your questions. Some common question types include:

• Scales with labels or numbers , for example ‘very good, fairly good, neither good nor poor, fairly poor, very poor’ or a scale of 1 to 5 with 1 being ‘very good’ and 5 being ‘very poor’. Scales should always be balanced with the same number of ‘positive’ options as ‘negative’ options and the two ends of the scales should be genuine polar opposites (e.g. ‘very good’ and ‘very poor’ rather than ‘excellent’ at one end and ‘very poor’ at the other end).
• Open questions , where a respondent answers in their own words and are best used when you don’t have a good idea of what the answer might be or if you want to collect quotes for example, ‘What have you enjoyed most about your time at university?’
• Closed questions , where an answer is selected from a pre-determined list. Be careful not to introduce any response bias by rotating the order in which response options appear so the same answer doesn’t always appear at the top of the list. Make sure important answers aren’t missing from the list – add an ‘Other (specify) as a safety net – or that two or more contradictory answers can’t both be selected.
• Ranking  used to find order of preference for items on a list. This type of question is most useful to differentiate between items when everything is obviously either a ‘good thing’ or a ‘bad thing’. The list should be limited to 7 or 8 items – for longer lists, asking for 1 st , 2 nd  and 3 rd  preference would be a better option.

Top Tip: Consider limiting the number of open questions you include in your survey – firstly they are more burdensome for the respondent to answer and secondly, they are more time consuming for you to analyse.

Question wording.

The way a question is worded is critical in how it is interpreted. Badly worded questions can lead to careless, inaccurate or dishonest answers. Keep in mind the following:

• Simplicity – keep language simple, but tailor it accordingly, how you ask questions to students will be different to how you ask them to employers.
• Length – use short sentences, but say enough to be specific (e.g. rather than ‘Where do you live?’ use ‘In what town or city do you live?’)
• Ambiguity – be aware of common words that are ambiguous and use definitions wherever necessary (for example, if asking ‘Do you  regularly  travel to the university campus by bus?’ include ‘By regularly, we mean at least twice a week).
• Assumption – keep in mind not everyone will be able to answer the question or know something (for example if asking an employer, ‘How often do you take on apprentices?’ this should be split into ‘Have you ever taken on an apprentice?’ and then  if yes  ‘In the last three years, how many apprentices have you taken on?’).
• Leading wording – Steer clear of phrasing that guides the respondent to an answer or implies certain responses are more ‘normal’ or expected.
• Avoid asking about more than one thing in the same question e.g. How would you rate your accommodation and the on-site support services? You won’t know if a student is rating the overall accommodation, the on-site support services or giving an average across the two.
• Avoid double-negatives, for example ‘Do you disagree with the university’s decision not to run face to face lectures this term? – Yes or No’ Such questions are difficult to understand and are likely to cause confusion and yield inaccurate answers.
• Memory limitations – err on the side of using shorter reference periods and avoid ambiguity by stating precise timeframes you are interested in.

Top tip: Once drafted, get a colleague to complete the survey to test comprehension and understanding and to see how long it takes to complete!

A few final pointers on format, accessibility and length.

As part of planning the project, you will have already decided how you are going to run your survey –online, telephone, or indeed a mix of these.

Remember,  how you run your survey can influence how questions are answered . For example, you want to ask an applicant a closed question – Why did you shortlist this university in your application?  When you display this question on an online survey, the applicant will see a list of response options to choose from. However, unless you  read out  these options in the equivalent telephone survey, they will not ‘have sight’ of them. Their exposure to the list of response options is different depending on how they are surveyed which may result in different answers being given.

Make sure you cater for all needs, for example large font or high contrast colours when completing an online survey for those with visual impairments or advance sight of the questions for those completing a telephone survey but are hard of hearing.

Typically, the shorter the questionnaire, the better. The longer a questionnaire is, the higher the dropout rate. As rule of thumb it is good practice to keep an online questionnaire to no more than 10 minutes, and a telephone questionnaire to 15 minutes.

Top tip: If you are running an online survey you should think about how each question will look visually. Make sure questions display correctly for all devices including mobile phones. Don’t let bad formatting put respondents off completing the survey!

28 Questionnaire Examples, Questions, & Templates to Survey Your Clients

Published: May 15, 2023

The adage "the customer is always right" has received some pushback in recent years, but when it comes to conducting surveys , the phrase is worth a deeper look. In the past, representatives were tasked with solving client problems as they happened. Now, they have to be proactive by solving problems before they come up.

Salesforce found that 63% of customers expect companies to anticipate their needs before they ask for help. But how can a customer service team recognize these customer needs in advance and effectively solve them on a day-to-day basis?

A customer questionnaire is a tried-and-true method for collecting survey data to inform your customer service strategy . By hearing directly from the customer, you'll capture first-hand data about how well your service team meets their needs. In this article, you'll get free questionnaire templates and best practices on how to administer them for the most honest responses.

Table of Contents:

Questionnaire Definition

Survey vs. questionnaire, questionnaire templates.

• Questionnaire Examples

Questionnaire Design

Survey question examples.

• Examples of Good Survey Questions

How to Make a Questionnaire

A questionnaire is a research tool used to conduct surveys. It includes specific questions with the goal to understand a topic from the respondents' point of view. Questionnaires typically have closed-ended, open-ended, short-form, and long-form questions.

The questions should always stay as unbiased as possible. For instance, it's unwise to ask for feedback on a specific product or service that’s still in the ideation phase. To complete the questionnaire, the customer would have to imagine how they might experience the product or service rather than sharing their opinion about their actual experience with it.

Ask broad questions about the kinds of qualities and features your customers enjoy in your products or services and incorporate that feedback into new offerings your team is developing.

What makes a good questionnaire?

Define the goal, make it short and simple, use a mix of question types, proofread carefully, keep it consistent.

A good questionnaire should find what you need versus what you want. It should be valuable and give you a chance to understand the respondent’s point of view.

Make the purpose of your questionnaire clear. While it's tempting to ask a range of questions simultaneously, you'll get more valuable results if you stay specific to a set topic.

According to HubSpot research , 47% of those surveyed say their top reason for abandoning a survey is the time it takes to complete.

So, questionnaires should be concise and easy to finish. If you're looking for a respondent’s experience with your business, focus on the most important questions.

5 Free Customer Satisfaction Survey Templates

Easily measure customer satisfaction and begin to improve your customer experience.

• Net Promoter Score
• Customer Effort Score

You're all set!

Click this link to access this resource at any time.

5 Customer Survey Templates

Featured resource.

Your questionnaire should include a combination of question types, like open-ended, long-form, or short-ended questions.

Open-ended questions give users a chance to share their own answers. But closed-ended questions are more efficient and easy to quantify, with specific answer choices.

If you're not sure which question types are best, read here for more survey question examples .

While it's important to check spelling and grammar, there are two other things you'll want to check for a great questionnaire.

First, edit for clarity. Jargon, technical terms, and brand-specific language can be confusing for respondents. Next, check for leading questions. These questions can produce biased results that will be less useful to your team.

Consistency makes it easier for respondents to quickly complete your questionnaire. This is because it makes the questions less confusing. It can also reduce bias.

Being consistent is also helpful for analyzing questionnaire data because it makes it easier to compare results. With this in mind, keep response scales, question types, and formatting consistent.

In-Depth Interviews vs. Questionnaire

Questionnaires can be a more feasible and efficient research method than in-depth interviews. They are a lot cheaper to conduct. That’s because in-depth interviews can require you to compensate the interviewees for their time and give accommodations and travel reimbursement.

Questionnaires also save time for both parties. Customers can quickly complete them on their own time, and employees of your company don't have to spend time conducting the interviews. They can capture a larger audience than in-depth interviews, making them much more cost-effective.

It would be impossible for a large company to interview tens of thousands of customers in person. The same company could potentially get feedback from its entire customer base using an online questionnaire.

When considering your current products and services (as well as ideas for new products and services), it's essential to get the feedback of existing and potential customers. They are the ones who have a say in purchasing decisions.

A questionnaire is a tool that’s used to conduct a survey. A survey is the process of gathering, sampling, analyzing, and interpreting data from a group of people.

The confusion between these terms most likely stems from the fact that questionnaires and data analysis were treated as very separate processes before the Internet became popular. Questionnaires used to be completed on paper, and data analysis occurred later as a separate process. Nowadays, these processes are typically combined since online survey tools allow questionnaire responses to be analyzed and aggregated all in one step.

But questionnaires can still be used for reasons other than data analysis. Job applications and medical history forms are examples of questionnaires that have no intention of being statistically analyzed. The key difference between questionnaires and surveys is that they can exist together or separately.

Below are some of the best free questionnaire templates you can download to gather data that informs your next product or service offering.

What makes a good survey question?

Have a goal in mind, draft clear and distinct answers and questions, ask one question at a time, check for bias and sensitivity, include follow-up questions.

To make a good survey question, you have to choose the right type of questions to use. Include concise, clear, and appropriate questions with answer choices that won’t confuse the respondent and will clearly offer data on their experience.

Good survey questions can give a business good data to examine. Here are some more tips to follow as you draft your survey questions.

To make a good survey, consider what you are trying to learn from it. Understanding why you need to do a survey will help you create clear and concise questions that you need to ask to meet your goal. The more your questions focus on one or two objectives, the better your data will be.

You have a goal in mind for your survey. Now you have to write the questions and answers depending on the form you’re using.

For instance, if you’re using ranks or multiple-choice in your survey, be clear. Here are examples of good and poor multiple-choice answers:

Poor Survey Question and Answer Example

California:

• Contains the tallest mountain in the United States.
• Has an eagle on its state flag.
• Is the second-largest state in terms of area.
• Was the location of the Gold Rush of 1849.

Good Survey Question and Answer Example

What is the main reason so many people moved to California in 1849?

• California's land was fertile, plentiful, and inexpensive.
• The discovery of gold in central California.
• The East was preparing for a civil war.
• They wanted to establish religious settlements.

In the poor example, the question may confuse the respondent because it's not clear what is being asked or how the answers relate to the question. The survey didn’t fully explain the question, and the options are also confusing.

In the good example above, the question and answer choices are clear and easy to understand.

Always make sure answers and questions are clear and distinct to create a good experience for the respondent. This will offer your team the best outcomes from your survey.

It's surprisingly easy to combine multiple questions into one. They even have a name — they’re called "double-barreled" questions. But a good survey asks one question at a time.

For example, a survey question could read, "What is your favorite sneaker and clothing apparel brand?" This is bad because you’re asking two questions at once.

By asking two questions simultaneously, you may confuse your respondents and get unclear answers. Instead, each question should focus on getting specific pieces of information.

For example, ask, "What is your favorite sneaker brand?" then, "What is your favorite clothing apparel brand?" By separating the questions, you allow your respondents to give separate and precise answers.

Biased questions can lead a respondent toward a specific response. They can also be vague or unclear. Sensitive questions such as age, religion, or marital status can be helpful for demographics. These questions can also be uncomfortable for people to answer.

There are a few ways to create a positive experience with your survey questions.

First, think about question placement. Sensitive questions that appear in context with other survey questions can help people understand why you are asking. This can make them feel more comfortable responding.

Next, check your survey for leading questions, assumptions, and double-barreled questions. You want to make sure that your survey is neutral and free of bias.

Asking more than one survey question about an area of interest can make a survey easier to understand and complete. It also helps you collect more in-depth insights from your respondents.

1. Free HubSpot Questionnaire Template

HubSpot offers a variety of free customer surveys and questionnaire templates to analyze and measure customer experience. Choose from five templates: net promoter score, customer satisfaction, customer effort, open-ended questions, and long-form customer surveys.

2. Client Questionnaire Template

It's a good idea to gauge your clients' experiences with your business to uncover opportunities to improve your offerings. That will, in turn, better suit their lifestyles. You don't have to wait for an entire year to pass before polling your customer base about their experience either. A simple client questionnaire, like the one below, can be administered as a micro survey several times throughout the year. These types of quick survey questions work well to retarget your existing customers through social media polls and paid interactive ads.

1. How much time do you spend using [product or service]?

• Less than a minute
• About 1 - 2 minutes
• Between 2 and 5 minutes
• More than 5 minutes

2. In the last month, what has been your biggest pain point?

• Finding enough time for important tasks
• Delegating work
• Having enough to do

3. What's your biggest priority right now?

• Finding a faster way to work
• Problem-solving
• Staff development

3. Website Questionnaire Template

Whether you just launched a brand new website or you're gathering data points to inform a redesign, you'll find customer feedback to be essential in both processes. A website questionnaire template will come in handy to collect this information using an unbiased method.

1. How many times have you visited [website] in the past month?

• More than once

2. What is the primary reason for your visit to [website]?

• To make a purchase
• To find more information before making a purchase in-store
• To contact customer service

3. Are you able to find what you're looking for on the website homepage?

4. Customer Satisfaction Questionnaire Template

If you've never surveyed your customers and are looking for a template to get started, this one includes some basic customer satisfaction questions. These will apply to just about any customer your business serves.

1. How likely are you to recommend us to family, friends, or colleagues?

• Extremely unlikely
• Somewhat unlikely
• Somewhat likely
• Extremely likely

2. How satisfied were you with your experience?

1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10

3. Rank the following items in terms of their priority to your purchasing process.

• Helpful staff
• Quality of product
• Price of product
• Ease of purchase
• Proximity of store
• Online accessibility
• Current need
• Appearance of product

4. Who did you purchase these products for?

• Family member
• On behalf of a business

5. Please rate our staff on the following terms:

• Friendly __ __ __ __ __ Hostile
• Helpful __ __ __ __ __ Useless
• Knowledgeable __ __ __ __ __ Inexperienced
• Professional __ __ __ __ __ Inappropriate

6. Would you purchase from our company again?

7. How can we improve your experience for the future?

________________________________.

5. Customer Effort Score Questionnaire Template

The following template gives an example of a brief customer effort score (CES) questionnaire. This free template works well for new customers to measure their initial reaction to your business.

1. What was the ease of your experience with our company?

• Extremely difficult
• Somewhat difficult
• Somewhat easy
• Extremely easy

2. The company did everything it could to make my process as easy as possible.

• Strongly disagree
• Somewhat disagree
• Somewhat agree
• Strongly agree

3. On a scale of 1 to 10 (1 being "extremely quickly" and 10 being "extremely slowly"), how fast were you able to solve your problem?

4. How much effort did you have to put forth while working with our company?

• Much more than expected
• Somewhat more than expected
• As much as expected
• Somewhat less than expected
• Much less than expected

6. Demographic Questionnaire Template

Here's a template for surveying customers to learn more about their demographic background. You could substantiate the analysis of this questionnaire by corroborating the data with other information from your web analytics, internal customer data, and industry data.

1. How would you describe your employment status?

• Employed full-time
• Employed part-time
• Freelance/contract employee
• Self-employed

2. How many employees work at your company?

3. How would you classify your role?

• Individual Contributor

4. How would you classify your industry?

• Technology/software
• Hospitality/dining
• Entertainment

Below, we have curated a list of questionnaire examples that do a great job of gathering valuable qualitative and quantitative data.

4 Questionnaire Examples

1. customer satisfaction questions.

Image Source

Rating Scale

Rating scale questions offer a scale of numbers and ask respondents to rate topics based on the sentiments assigned to that scale. This is effective when assessing customer satisfaction.

Rating scale survey question examples : "Rate your level of satisfaction with the customer service you received today on a scale of 1-10."

Yes or no survey questions are a type of dichotomous question. These are questions that only offer two possible responses. They’re useful because they’re quick to answer and can help with customer segmentation.

Yes or no survey questions example : "Have you ever used HubSpot before?"

Likert Scale

Likert scale questions assess whether a respondent agrees with the statement, as well as the extent to which they agree or disagree.

These questions typically offer five or seven responses, with sentiments ranging from items such as "strongly disagree" to "strongly agree." Check out this post to learn more about the Likert scale .

Likert scale survey question examples : “How satisfied are you with the service from [brand]?”

Open-ended questions ask a broader question or offer a chance to elaborate on a response to a close-ended question. They're accompanied by a text box that leaves room for respondents to write freely. This is particularly important when asking customers to expand on an experience or recommendation.

Open-ended survey question examples : "What are your personal goals for using HubSpot? Please describe."

Matrix Table

A matrix table is usually a group of multiple-choice questions grouped in a table. Choices for these survey questions are usually organized in a scale. This makes it easier to understand the relationships between different survey responses.

Matrix table survey question examples : "Rate your level of agreement with the following statements about HubSpot on a scale of 1-5."

Rank Order Scaling

These questions ask respondents to rank a set of terms by order of preference or importance. This is useful for understanding customer priorities.

Rank order scaling examples : "Rank the following factors in order of importance when choosing a new job."

Semantic Differential Scale

This scale features pairs of opposite adjectives that respondents use for rating, usually for a feature or experience. This type of question makes it easier to understand customer attitudes and beliefs.

Semantic differential scale question examples : "Rate your overall impression of this brand as friendly vs. unfriendly, innovative vs. traditional, and boring vs. exciting."

Side-By-Side Matrix

This matrix table format includes two sets of questions horizontally for easy comparison. This format can help with customer gap analysis.

Side-by-side matrix question examples : "Rate your level of satisfaction with HubSpot's customer support compared to its ease of use."

Stapel Scale

The Stapel rating scale offers a single adjective or idea for rating. It uses a numerical scale with a zero point in the middle. This survey question type helps with in-depth analysis.

Stapel scale survey question examples : "Rate your overall experience with this product as +5 (excellent) to -5 (terrible)."

Constant Sum Survey Questions

In this question format, people distribute points to different choices based on the perceived importance of each point. This kind of question is often used in market research and can help your team better understand customer choices .

Constant sum survey question examples : "What is your budget for the following marketing expenses: Paid campaigns, Events, Freelancers, Agencies, Research."

Image Choice

This survey question type shows several images. Then, it asks the respondent to choose the image that best matches their response to the question. These questions are useful for understanding your customers’ design preferences.

Image choice survey questions example : "Which of these three images best represents your brand voice?"

Choice Model

This survey question offers a hypothetical scenario, then the respondent must choose from the presented options. It's a useful type of question when you are refining a product or strategy.

Choice model survey questions example : "Which of these three deals would be most appealing to you?"

Click Map Questions

Click map questions offer an image click on specific areas of the image in response to a question. This question uses data visualization to learn about customer preferences for design and user experience.

Click map question examples : "Click on the section of the website where you would expect to find pricing information."

Data Upload

This survey question example asks the respondent to upload a file or document in response to a question. This type of survey question can help your team collect data and context that might be tough to collect otherwise.

Data upload question examples : "Please upload a screenshot of the error you encountered during your purchase."

Benchmarkable Questions

This question type asks a respondent to compare their answers to a group or benchmark. These questions can be useful if you're trying to compare buyer personas or other customer groups.

Benchmarkable survey questions example : "Compare your company's marketing budget to other companies in your industry."

Good Survey Questions

• What is your favorite product?
• Why did you purchase this product?
• How satisfied are you with [product]?
• Would you recommend [product] to a friend?
• Would you recommend [company name] to a friend?
• If you could change one thing about [product], what would it be?
• Which other options were you considering before [product or company name]?
• Did [product] help you accomplish your goal?
• How would you feel if we did not offer this product, feature, or service?
• What would you miss the most if you couldn't use your favorite product from us?
• What is one word that best describes your experience using our product?
• What's the primary reason for canceling your account?
• How satisfied are you with our customer support?
• Did we answer all of your questions and concerns?
• How can we be more helpful?
• What additional features would you like to see in this product?
• Are we meeting your expectations?
• How satisfied are you with your experience?

1. "What is your favorite product?"

This question is a great starter for your survey. Most companies want to know what their most popular products are, and this question cuts right to the point.

It's important to note that this question gives you the customer's perspective, not empirical evidence. You should compare the results to your inventory to see if your customers' answers match your actual sales. You may be surprised to find your customers' "favorite" product isn't the highest-selling one.

2. "Why did you purchase this product?"

Once you know their favorite product, you need to understand why they like it so much. The qualitative data will help your marketing and sales teams attract and engage customers. They'll know which features to advertise most and can seek out new leads similar to your existing customers.

3. "How satisfied are you with [product]?"

When you have a product that isn't selling, you can ask this question to see why customers are unhappy with it. If the reviews are poor, you'll know that the product needs reworking, and you can send it back to product management for improvement. Or, if these results are positive, they may have something to do with your marketing or sales techniques. You can then gather more info during the questionnaire and restrategize your campaigns based on your findings.

4. "Would you recommend [product] to a friend?"

This is a classic survey question used with most NPS® surveys. It asks the customer if they would recommend your product to one of their peers. This is extremely important because most people trust customer referrals more than traditional advertising. So, if your customers are willing to recommend your products, you'll have an easier time acquiring new leads.

5. "Would you recommend [company name] to a friend?"

Similar to the question above, this one asks the customer to consider your business as a whole and not just your product. This gives you insight into your brand's reputation and shows how customers feel about your company's actions. Even if you have an excellent product, your brand's reputation may be the cause of customer churn . Your marketing team should pay close attention to this question to see how they can improve the customer experience .

6. "If you could change one thing about [product], what would it be?"

This is a good question to ask your most loyal customers or ones that have recently churned. For loyal customers, you want to keep adding value to their experience. Asking how your product can improve helps your development team find flaws and increases your chances of retaining a valuable customer segment.

For customers that have recently churned, this question gives insight into how you can retain future users that are unhappy with your product or service. By giving these customers a space to voice their criticisms, you can either reach out and offer solutions or relay feedback for consideration.

7. "Which other options were you considering before [product or company name]?"

If you're operating in a competitive industry, customers will have more than one choice when considering your brand. And if you sell variations of your product or produce new models periodically, customers may prefer one version over another.

For this question, you should offer answers to choose from in a multiple-selection format. This will limit the types of responses you'll receive and help you get the exact information you need.

8. "Did [product] help you accomplish your goal?"

The purpose of any product or service is to help customers reach a goal. So, you should be direct and ask them if your company steered them toward success. After all, customer success is an excellent retention tool. If customers are succeeding with your product, they're more likely to stay loyal to your brand.

9. "How would you feel if we did not offer this product, feature, or service?"

Thinking about discontinuing a product? This question can help you decide whether or not a specific product, service, or feature will be missed if you were to remove it.

Even if you know that a product or service isn't worth offering, it's important to ask this question anyway because there may be a certain aspect of the product that your customers like. They'll be delighted if you can integrate that feature into a new product or service.

10. "If you couldn't use your favorite product from us, what would you miss the most about it?"

This question pairs well with the one above because it frames the customer's favorite product from a different point of view. Instead of describing why they love a particular product, the customer can explain what they'd be missing if they didn't have it at all. This type of question uncovers "fear of loss," which can be a very different motivating factor than "hope for gain."

11. "What word best describes your experience using our product?"

Your marketing team will love this question. A single word or a short phrase can easily sum up your customers’ emotions when they experience your company, product, or brand. Those emotions can be translated into relatable marketing campaigns that use your customers’ exact language.

If the responses reveal negative emotions, it's likely that your entire customer service team can relate to that pain point. Rather than calling it "a bug in the system," you can describe the problem as a "frustrating roadblock" to keep their experience at the forefront of the solution.

12. "What's the primary reason for canceling your account?"

Finding out why customers are unhappy with your product or service is key to decreasing your churn rate . If you don't understand why people leave your brand, it's hard to make effective changes to prevent future turnover. Or worse, you might alter your product or service in a way that increases your churn rate, causing you to lose customers who were once loyal supporters.

13. "How satisfied are you with our customer support?"

It's worth asking customers how happy they are with your support or service team. After all, an excellent product doesn't always guarantee that customers will stay loyal to your brand. Research shows that one in six customers will leave a brand they love after just one poor service experience.

14. "Did we answer all of your questions and concerns?"

This is a good question to ask after a service experience. It shows how thorough your support team is and whether they're prioritizing speed too much over quality. If customers still have questions and concerns after a service interaction, your support team is focusing too much on closing tickets and not enough on meeting customer needs .

15. "How can we be more helpful?"

Sometimes it's easier to be direct and simply ask customers what else you can do to help them. This shows a genuine interest in your buyers' goals which helps your brand foster meaningful relationships with its customer base. The more you can show that you sincerely care about your customers' problems, the more they'll open up to you and be honest about how you can help them.

16. What additional features would you like to see in this product?

With this question, your team can get inspiration for the company's next product launch. Think of the responses as a wish list from your customers. You can discover what features are most valuable to them and whether they already exist within a competitor's product.

Incorporating every feature suggestion is nearly impossible, but it's a convenient way to build a backlog of ideas that can inspire future product releases.

17. "Are we meeting your expectations?"

This is a really important question to ask because customers won't always tell you when they're unhappy with your service. Not every customer will ask to speak with a manager when they're unhappy with your business. In fact, most will quietly move on to a competitor rather than broadcast their unhappiness to your company. To prevent this type of customer churn, you need to be proactive and ask customers if your brand is meeting their expectations.

18. "How satisfied are you with your experience?"

This question asks the customer to summarize their experience with your business. It gives you a snapshot of how the customer is feeling in that moment and their perception of your brand. Asking this question at the right stage in the customer's journey can tell you a lot about what your company is doing well and where you can stand to improve.

Next, let's dig into some tips for creating your own questionnaire.

Start with templates as a foundation. Know your question types. Keep it brief when possible. Choose a simple visual design. Use a clear research process. Create questions with straightforward, unbiased language. Make sure every question is important. Ask one question at a time. Order your questions logically. Consider your target audience. Test your questionnaire.

1. Use questionnaire templates.

Rather than build a questionnaire from scratch, consider using questionnaire templates to get started. HubSpot's collection of customer-facing questionnaire templates can help you quickly build and send a questionnaire to your clients and analyze the results right on Google Drive.

Vrnda LeValley , customer training manager at HubSpot, recommends starting with an alignment question like, "Does this class meet your expectations?" because it gives more context to any positive or negative scores that follow. She continues, "If it didn't meet expectations, then there will potentially be negative responses across the board (as well as the reverse)."

3. Keep it brief, when possible.

Most questionnaires don't need to be longer than a page. For routine customer satisfaction surveys, it's unnecessary to ask 50 slightly varied questions about a customer's experience when those questions could be combined into 10 solid questions.

The shorter your questionnaire is, the more likely a customer will complete it. Plus a shorter questionnaire means less data for your team to collect and analyze. Based on the feedback, it will be a lot easier for you to get the information you need to make the necessary changes in your organization and products.

4. Choose a simple visual design.

There's no need to make your questionnaire a stunning work of art. As long as it's clear and concise, it will be attractive to customers. When asking questions that are important to furthering your company, it's best to keep things simple. Select a font that’s common and easy to read, like Helvetica or Arial. Use a text size that customers of all abilities can navigate.

A questionnaire is most effective when all the questions are visible on a single screen. The layout is important. If a questionnaire is even remotely difficult to navigate, your response rate could suffer. Make sure that buttons and checkboxes are easy to click and that questions are visible on both computer and mobile screens.

5. Use a clear research process.

Before planning questions for your questionnaire, you'll need to have a definite direction for it. A questionnaire is only effective if the results answer an overarching research question. After all, the research process is an important part of the survey, and a questionnaire is a tool that's used within the process.

In your research process, you should first come up with a research question. What are you trying to find out? What's the point of this questionnaire? Keep this in mind throughout the process.

After coming up with a research question, it's a good idea to have a hypothesis. What do you predict the results will be for your questionnaire? This can be structured in a simple "If … then …" format. A structured experiment — yes, your questionnaire is a type of experiment — will confirm that you're only collecting and analyzing data necessary to answer your research question. Then, you can move forward with your survey .

6. Create questions with straightforward, unbiased language.

When crafting your questions, it's important to structure them to get the point across. You don't want any confusion for your customers because this may influence their answers. Instead, use clear language. Don't use unnecessary jargon, and use simple terms in favor of longer-winded ones.

You may risk the reliability of your data if you try to combine two questions. Rather than asking, "How was your experience shopping with us, and would you recommend us to others?" separate it into two separate questions. Customers will be clear on your question and choose a response most appropriate for each one.

You should always keep the language in your questions unbiased. You never want to sway customers one way or another because this will cause your data to be skewed. Instead of asking, "Some might say that we create the best software products in the world. Would you agree or disagree?" it may be better to ask, "How would you rate our software products on a scale of 1 to 10?" This removes any bias and confirms that all the responses are valid.

7. Ask only the most important questions.

When creating your questionnaire, keep in mind that time is one of the most valuable commodities for customers. Most aren't going to sit through a 50-question survey, especially when they're being asked about products or services they didn't use. Even if they do complete it, most of these will be half-hearted responses from fatigued customers who simply want to be finished with it.

If your questionnaire has five or 55 questions, make sure each has a specific purpose. Individually, they should be aimed at collecting certain pieces of information that reveal new insights into different aspects of your business. If your questions are irrelevant or seem out of place, your customers will be easily derailed by the survey. And, once the customer has lost interest, it'll be difficult to regain their focus.

8. Ask one question at a time.

Since every question has a purpose, ask them one at a time. This lets the customer focus and encourages them to share a thoughtful response. This is particularly important for open-ended questions where customers need to describe an experience or opinion.

By grouping questions together, you risk overwhelming busy customers who don't have time for a long survey. They may think you're asking them too much, or they might see your questionnaire as a daunting task. You want your survey to appear as painless as possible. Keeping your questions separated will make it more user-friendly.

9. Order your questions logically.

A good questionnaire is like a good book. The beginning questions should lay the framework, the middle ones should cut to the core issues, and the final questions should tie up all loose ends. This flow keeps customers engaged throughout the entire survey.

When creating your questionnaire, start with the most basic questions about demographics. You can use this information to segment your customer base and create different buyer personas.

Next, add in your product and services questions. These are the ones that offer insights into common customer roadblocks and where you can improve your business's offerings. Questions like these guide your product development and marketing teams looking for new ways to enhance the customer experience.

Finally, you should conclude your questionnaire with open-ended questions to understand the customer journey. These questions let customers voice their opinions and point out specific experiences they've had with your brand.

10. Consider your target audience.

Whenever you collect customer feedback, you need to keep in mind the goals and needs of your target audience. After all, the participants in this questionnaire are your active customers. Your questions should be geared toward the interests and experiences they've already had with your company.

You can even create multiple surveys that target different buyer personas. For example, if you have a subscription-based pricing model, you can personalize your questionnaire for each type of subscription your company offers.

11. Test your questionnaire.

Once your questionnaire is complete, it's important to test it. If you don't, you may end up asking the wrong questions and collecting irrelevant or inaccurate information. Start by giving your employees the questionnaire to test, then send it to small groups of customers and analyze the results. If you're gathering the data you're looking for, then you should release the questionnaire to all of your customers.

How Questionnaires Can Benefit Your Customer Service Strategy

Whether you have one customer or 1000 customers, their opinions matter when it comes to the success of your business. Their satisfaction with your offerings can reveal how well or how poorly your customer service strategy and business are meeting their needs. A questionnaire is one of the most powerful, cost-effective tools to uncover what your customers think about your business. When analyzed properly, it can inform your product and service launches.

Use the free questionnaire templates, examples, and best practices in this guide to conduct your next customer feedback survey.

Now that you know the slight difference between a survey and a questionnaire, it’s time to put it into practice with your products or services. Remember, a good survey and questionnaire always start with a purpose. But, a great survey and questionnaire give data that you can use to help companies increase the way customers respond to their products or services because of the questions.

Net Promoter, Net Promoter System, Net Promoter Score, NPS, and the NPS-related emoticons are registered trademarks of Bain & Company, Inc., Fred Reichheld, and Satmetrix Systems, Inc.

Editor's note: This post was originally published in July 2018 and has been updated for comprehensiveness.

Don't forget to share this post!

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Designing and validating a research questionnaire - Part 1

Priya ranganathan.

Department of Anaesthesiology, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India

Carlo Caduff

1 Department of Global Health and Social Medicine, King’s College London, London, United Kingdom

Questionnaires are often used as part of research studies to collect data from participants. However, the information obtained through a questionnaire is dependent on how it has been designed, used, and validated. In this article, we look at the types of research questionnaires, their applications and limitations, and how a new questionnaire is developed.

INTRODUCTION

In research studies, questionnaires are commonly used as data collection tools, either as the only source of information or in combination with other techniques in mixed-method studies. However, the quality and accuracy of data collected using a questionnaire depend on how it is designed, used, and validated. In this two-part series, we discuss how to design (part 1) and how to use and validate (part 2) a research questionnaire. It is important to emphasize that questionnaires seek to gather information from other people and therefore entail a social relationship between those who are doing the research and those who are being researched. This social relationship comes with an obligation to learn from others , an obligation that goes beyond the purely instrumental rationality of gathering data. In that sense, we underscore that any research method is not simply a tool but a situation, a relationship, a negotiation, and an encounter. This points to both ethical questions (what is the relationship between the researcher and the researched?) and epistemological ones (what are the conditions under which we can know something?).

At the start of any kind of research project, it is crucial to select the right methodological approach. What is the research question, what is the research object, and what can a questionnaire realistically achieve? Not every research question and not every research object are suitable to the questionnaire as a method. Questionnaires can only provide certain kinds of empirical evidence and it is thus important to be aware of the limitations that are inherent in any kind of methodology.

WHAT IS A RESEARCH QUESTIONNAIRE?

A research questionnaire can be defined as a data collection tool consisting of a series of questions or items that are used to collect information from respondents and thus learn about their knowledge, opinions, attitudes, beliefs, and behavior and informed by a positivist philosophy of the natural sciences that consider methods mainly as a set of rules for the production of knowledge; questionnaires are frequently used instrumentally as a standardized and standardizing tool to ask a set of questions to participants. Outside of such a positivist philosophy, questionnaires can be seen as an encounter between the researcher and the researched, where knowledge is not simply gathered but negotiated through a distinct form of communication that is the questionnaire.

STRENGTHS AND LIMITATIONS OF QUESTIONNAIRES

A questionnaire may not always be the most appropriate way of engaging with research participants and generating knowledge that is needed for a research study. Questionnaires have advantages that have made them very popular, especially in quantitative studies driven by a positivist philosophy: they are a low-cost method for the rapid collection of large amounts of data, even from a wide sample. They are practical, can be standardized, and allow comparison between groups and locations. However, it is important to remember that a questionnaire only captures the information that the method itself (as the structured relationship between the researcher and the researched) allows for and that the respondents are willing to provide. For example, a questionnaire on diet captures what the respondents say they eat and not what they are eating. The problem of social desirability emerges precisely because the research process itself involves a social relationship. This means that respondents may often provide socially acceptable and idealized answers, particularly in relation to sensitive questions, for example, alcohol consumption, drug use, and sexual practices. Questionnaires are most useful for studies investigating knowledge, beliefs, values, self-understandings, and self-perceptions that reflect broader social, cultural, and political norms that may well diverge from actual practices.

TYPES OF RESEARCH QUESTIONNAIRES

Research questionnaires may be classified in several ways:

Depending on mode of administration

Research questionnaires may be self-administered (by the research participant) or researcher administered. Self-administered (also known as self-reported or self-completed) questionnaires are designed to be completed by respondents without assistance from a researcher. Self-reported questionnaires may be administered to participants directly during hospital or clinic visits, mailed through the post or E-mail, or accessed through websites. This technique allows respondents to answer at their own pace and simplifies research costs and logistics. The anonymity offered by self-reporting may facilitate more accurate answers. However, the disadvantages are that there may be misinterpretations of questions and low response rates. Significantly, relevant context information is missing to make sense of the answers provided. Researcher-reported (or interviewer-reported) questionnaires may be administered face-to-face or through remote techniques such as telephone or videoconference and are associated with higher response rates. They allow the researcher to have a better understanding of how the data are collected and how answers are negotiated, but are more resource intensive and require more training from the researchers.

The choice between self-administered and researcher-administered questionnaires depends on various factors such as the characteristics of the target audience (e.g., literacy and comprehension level and ability to use technology), costs involved, and the need for confidentiality/privacy.

Depending on the format of the questions

Research questionnaires can have structured or semi-structured formats. Semi-structured questionnaires allow respondents to answer more freely and on their terms, with no restrictions on their responses. They allow for unusual or surprising responses and are useful to explore and discover a range of answers to determine common themes. Typically, the analysis of responses to open-ended questions is more complex and requires coding and analysis. In contrast, structured questionnaires provide a predefined set of responses for the participant to choose from. The use of standard items makes the questionnaire easier to complete and allows quick aggregation, quantification, and analysis of the data. However, structured questionnaires can be restrictive if the scope of responses is limited and may miss potential answers. They also may suggest answers that respondents may not have considered before. Respondents may be forced to fit their answers into the predetermined format and may not be able to express personal views and say what they really want to say or think. In general, this type of questionnaire can turn the research process into a mechanical, anonymous survey with little incentive for participants to feel engaged, understood, and taken seriously.

STRUCTURED QUESTIONS: FORMATS

Some examples of close-ended questions include:

e.g., Please indicate your marital status:

• Prefer not to say.

e.g., Describe your areas of work (circle or tick all that apply):

• Clinical service
• Administration
• Strongly agree
• Strongly disagree.
• Numerical scales: Please rate your current pain on a scale of 1–10 where 1 is no pain and 10 is the worst imaginable pain
• Symbolic scales: For example, the Wong-Baker FACES scale to rate pain in older children
• Ranking: Rank the following cities as per the quality of public health care, where 1 is the best and 5 is the worst.

A matrix questionnaire consists of a series of rows with items to be answered with a series of columns providing the same answer options. This is an efficient way of getting the respondent to provide answers to multiple questions. The EORTC QLQ-C30 is an example of a matrix questionnaire.[ 1 ]

For a more detailed review of the types of research questions, readers are referred to a paper by Boynton and Greenhalgh.[ 2 ]

USING PRE-EXISTING QUESTIONNAIRES VERSUS DEVELOPING A NEW QUESTIONNAIRE

Before developing a questionnaire for a research study, a researcher can check whether there are any preexisting-validated questionnaires that might be adapted and used for the study. The use of validated questionnaires saves time and resources needed to design a new questionnaire and allows comparability between studies.

However, certain aspects need to be kept in mind: is the population/context/purpose for which the original questionnaire was designed similar to the new study? Is cross-cultural adaptation required? Are there any permission needed to use the questionnaire? In many situations, the development of a new questionnaire may be more appropriate given that any research project entails both methodological and epistemological questions: what is the object of knowledge and what are the conditions under which it can be known? It is important to understand that the standardizing nature of questionnaires contributes to the standardization of objects of knowledge. Thus, the seeming similarity in the object of study across diverse locations may be an artifact of the method. Whatever method one uses, it will always operate as the ground on which the object of study is known.

DESIGNING A NEW RESEARCH QUESTIONNAIRE

Once the researcher has decided to design a new questionnaire, several steps should be considered:

Gathering content

It creates a conceptual framework to identify all relevant areas for which the questionnaire will be used to collect information. This may require a scoping review of the published literature, appraising other questionnaires on similar topics, or the use of focus groups to identify common themes.

Create a list of questions

Questions need to be carefully formulated with attention to language and wording to avoid ambiguity and misinterpretation. Table 1 lists a few examples of poorlyworded questions that could have been phrased in a more appropriate manner. Other important aspects to be noted are:

Examples of poorly phrased questions in a research questionnaire

• Provide a brief introduction to the research study along with instructions on how to complete the questionnaire
• Allow respondents to indicate levels of intensity in their replies, so that they are not forced into “yes” or “no” answers where intensity of feeling may be more appropriate
• Collect specific and detailed data wherever possible – this can be coded into categories. For example, age can be captured in years and later classified as <18 years, 18–45 years, 46 years, and above. The reverse is not possible
• Avoid technical terms, slang, and abbreviations. Tailor the reading level to the expected education level of respondents
• The format of the questionnaire should be attractive with different sections for various subtopics. The font should be large and easy to read, especially if the questionnaire is targeted at the elderly
• Question sequence: questions should be arranged from general to specific, from easy to difficult, from facts to opinions, and sensitive topics should be introduced later in the questionnaire.[ 3 ] Usually, demographic details are captured initially followed by questions on other aspects
• Use contingency questions: these are questions which need to be answered only by a subgroup of the respondents who provide a particular answer to a previous question. This ensures that participants only respond to relevant sections of the questionnaire, for example, Do you smoke? If yes, then how long have you been smoking? If not, then please go to the next section.

TESTING A QUESTIONNAIRE

A questionnaire needs to be valid and reliable, and therefore, any new questionnaire needs to be pilot tested in a small sample of respondents who are representative of the larger population. In addition to validity and reliability, pilot testing provides information on the time taken to complete the questionnaire and whether any questions are confusing or misleading and need to be rephrased. Validity indicates that the questionnaire measures what it claims to measure – this means taking into consideration the limitations that come with any questionnaire-based study. Reliability means that the questionnaire yields consistent responses when administered repeatedly even by different researchers, and any variations in the results are due to actual differences between participants and not because of problems with the interpretation of the questions or their responses. In the next article in this series, we will discuss methods to determine the reliability and validity of a questionnaire.

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• Questionnaire Design | Methods, Question Types & Examples

Questionnaire Design | Methods, Question Types & Examples

Published on 6 May 2022 by Pritha Bhandari . Revised on 10 October 2022.

A questionnaire is a list of questions or items used to gather data from respondents about their attitudes, experiences, or opinions. Questionnaires can be used to collect quantitative and/or qualitative information.

Questionnaires are commonly used in market research as well as in the social and health sciences. For example, a company may ask for feedback about a recent customer service experience, or psychology researchers may investigate health risk perceptions using questionnaires.

Table of contents

Questionnaires vs surveys, questionnaire methods, open-ended vs closed-ended questions, question wording, question order, step-by-step guide to design, frequently asked questions about questionnaire design.

A survey is a research method where you collect and analyse data from a group of people. A questionnaire is a specific tool or instrument for collecting the data.

Designing a questionnaire means creating valid and reliable questions that address your research objectives, placing them in a useful order, and selecting an appropriate method for administration.

But designing a questionnaire is only one component of survey research. Survey research also involves defining the population you’re interested in, choosing an appropriate sampling method , administering questionnaires, data cleaning and analysis, and interpretation.

Sampling is important in survey research because you’ll often aim to generalise your results to the population. Gather data from a sample that represents the range of views in the population for externally valid results. There will always be some differences between the population and the sample, but minimising these will help you avoid sampling bias .

Prevent plagiarism, run a free check.

Questionnaires can be self-administered or researcher-administered . Self-administered questionnaires are more common because they are easy to implement and inexpensive, but researcher-administered questionnaires allow deeper insights.

Self-administered questionnaires

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or by post. All questions are standardised so that all respondents receive the same questions with identical wording.

Self-administered questionnaires can be:

• Cost-effective
• Easy to administer for small and large groups
• Anonymous and suitable for sensitive topics

But they may also be:

• Unsuitable for people with limited literacy or verbal skills
• Susceptible to a nonreponse bias (most people invited may not complete the questionnaire)
• Biased towards people who volunteer because impersonal survey requests often go ignored

Researcher-administered questionnaires

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents.

Researcher-administered questionnaires can:

• Help you ensure the respondents are representative of your target audience
• Allow clarifications of ambiguous or unclear questions and answers
• Have high response rates because it’s harder to refuse an interview when personal attention is given to respondents

But researcher-administered questionnaires can be limiting in terms of resources. They are:

• Costly and time-consuming to perform
• More difficult to analyse if you have qualitative responses
• Likely to contain experimenter bias or demand characteristics
• Likely to encourage social desirability bias in responses because of a lack of anonymity

Your questionnaire can include open-ended or closed-ended questions, or a combination of both.

Using closed-ended questions limits your responses, while open-ended questions enable a broad range of answers. You’ll need to balance these considerations with your available time and resources.

Closed-ended questions

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. Closed-ended questions are best for collecting data on categorical or quantitative variables.

Categorical variables can be nominal or ordinal. Quantitative variables can be interval or ratio. Understanding the type of variable and level of measurement means you can perform appropriate statistical analyses for generalisable results.

Examples of closed-ended questions for different variables

Nominal variables include categories that can’t be ranked, such as race or ethnicity. This includes binary or dichotomous categories.

It’s best to include categories that cover all possible answers and are mutually exclusive. There should be no overlap between response items.

In binary or dichotomous questions, you’ll give respondents only two options to choose from.

White Black or African American American Indian or Alaska Native Asian Native Hawaiian or Other Pacific Islander

Ordinal variables include categories that can be ranked. Consider how wide or narrow a range you’ll include in your response items, and their relevance to your respondents.

Likert-type questions collect ordinal data using rating scales with five or seven points.

When you have four or more Likert-type questions, you can treat the composite data as quantitative data on an interval scale . Intelligence tests, psychological scales, and personality inventories use multiple Likert-type questions to collect interval data.

With interval or ratio data, you can apply strong statistical hypothesis tests to address your research aims.

Pros and cons of closed-ended questions

Well-designed closed-ended questions are easy to understand and can be answered quickly. However, you might still miss important answers that are relevant to respondents. An incomplete set of response items may force some respondents to pick the closest alternative to their true answer. These types of questions may also miss out on valuable detail.

To solve these problems, you can make questions partially closed-ended, and include an open-ended option where respondents can fill in their own answer.

Open-ended questions

Open-ended, or long-form, questions allow respondents to give answers in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered. For example, respondents may want to answer ‘multiracial’ for the question on race rather than selecting from a restricted list.

• How do you feel about open science?
• How would you describe your personality?
• In your opinion, what is the biggest obstacle to productivity in remote work?

Open-ended questions have a few downsides.

They require more time and effort from respondents, which may deter them from completing the questionnaire.

For researchers, understanding and summarising responses to these questions can take a lot of time and resources. You’ll need to develop a systematic coding scheme to categorise answers, and you may also need to involve other researchers in data analysis for high reliability .

Question wording can influence your respondents’ answers, especially if the language is unclear, ambiguous, or biased. Good questions need to be understood by all respondents in the same way ( reliable ) and measure exactly what you’re interested in ( valid ).

Use clear language

You should design questions with your target audience in mind. Consider their familiarity with your questionnaire topics and language and tailor your questions to them.

For readability and clarity, avoid jargon or overly complex language. Don’t use double negatives because they can be harder to understand.

Use balanced framing

Respondents often answer in different ways depending on the question framing. Positive frames are interpreted as more neutral than negative frames and may encourage more socially desirable answers.

Use a mix of both positive and negative frames to avoid bias , and ensure that your question wording is balanced wherever possible.

Unbalanced questions focus on only one side of an argument. Respondents may be less likely to oppose the question if it is framed in a particular direction. It’s best practice to provide a counterargument within the question as well.

Avoid leading questions

Leading questions guide respondents towards answering in specific ways, even if that’s not how they truly feel, by explicitly or implicitly providing them with extra information.

It’s best to keep your questions short and specific to your topic of interest.

• The average daily work commute in the US takes 54.2 minutes and costs $29 per day. Since 2020, working from home has saved many employees time and money. Do you favour flexible work-from-home policies even after it’s safe to return to offices?
• Experts agree that a well-balanced diet provides sufficient vitamins and minerals, and multivitamins and supplements are not necessary or effective. Do you agree or disagree that multivitamins are helpful for balanced nutrition?

Keep your questions focused

Ask about only one idea at a time and avoid double-barrelled questions. Double-barrelled questions ask about more than one item at a time, which can confuse respondents.

This question could be difficult to answer for respondents who feel strongly about the right to clean drinking water but not high-speed internet. They might only answer about the topic they feel passionate about or provide a neutral answer instead – but neither of these options capture their true answers.

Instead, you should ask two separate questions to gauge respondents’ opinions.

Strongly Agree Agree Undecided Disagree Strongly Disagree

Do you agree or disagree that the government should be responsible for providing high-speed internet to everyone?

You can organise the questions logically, with a clear progression from simple to complex. Alternatively, you can randomise the question order between respondents.

Logical flow

Using a logical flow to your question order means starting with simple questions, such as behavioural or opinion questions, and ending with more complex, sensitive, or controversial questions.

The question order that you use can significantly affect the responses by priming them in specific directions. Question order effects, or context effects, occur when earlier questions influence the responses to later questions, reducing the validity of your questionnaire.

While demographic questions are usually unaffected by order effects, questions about opinions and attitudes are more susceptible to them.

• How knowledgeable are you about Joe Biden’s executive orders in his first 100 days?
• Are you satisfied or dissatisfied with the way Joe Biden is managing the economy?
• Do you approve or disapprove of the way Joe Biden is handling his job as president?

It’s important to minimise order effects because they can be a source of systematic error or bias in your study.

Randomisation

Randomisation involves presenting individual respondents with the same questionnaire but with different question orders.

When you use randomisation, order effects will be minimised in your dataset. But a randomised order may also make it harder for respondents to process your questionnaire. Some questions may need more cognitive effort, while others are easier to answer, so a random order could require more time or mental capacity for respondents to switch between questions.

Follow this step-by-step guide to design your questionnaire.

Step 1: Define your goals and objectives

The first step of designing a questionnaire is determining your aims.

• What topics or experiences are you studying?
• What specifically do you want to find out?
• Is a self-report questionnaire an appropriate tool for investigating this topic?

Once you’ve specified your research aims, you can operationalise your variables of interest into questionnaire items. Operationalising concepts means turning them from abstract ideas into concrete measurements. Every question needs to address a defined need and have a clear purpose.

Step 2: Use questions that are suitable for your sample

Create appropriate questions by taking the perspective of your respondents. Consider their language proficiency and available time and energy when designing your questionnaire.

• Are the respondents familiar with the language and terms used in your questions?
• Would any of the questions insult, confuse, or embarrass them?
• Do the response items for any closed-ended questions capture all possible answers?
• Are the response items mutually exclusive?
• Do the respondents have time to respond to open-ended questions?

Consider all possible options for responses to closed-ended questions. From a respondent’s perspective, a lack of response options reflecting their point of view or true answer may make them feel alienated or excluded. In turn, they’ll become disengaged or inattentive to the rest of the questionnaire.

Step 3: Decide on your questionnaire length and question order

Once you have your questions, make sure that the length and order of your questions are appropriate for your sample.

If respondents are not being incentivised or compensated, keep your questionnaire short and easy to answer. Otherwise, your sample may be biased with only highly motivated respondents completing the questionnaire.

Decide on your question order based on your aims and resources. Use a logical flow if your respondents have limited time or if you cannot randomise questions. Randomising questions helps you avoid bias, but it can take more complex statistical analysis to interpret your data.

Step 4: Pretest your questionnaire

When you have a complete list of questions, you’ll need to pretest it to make sure what you’re asking is always clear and unambiguous. Pretesting helps you catch any errors or points of confusion before performing your study.

Ask friends, classmates, or members of your target audience to complete your questionnaire using the same method you’ll use for your research. Find out if any questions were particularly difficult to answer or if the directions were unclear or inconsistent, and make changes as necessary.

If you have the resources, running a pilot study will help you test the validity and reliability of your questionnaire. A pilot study is a practice run of the full study, and it includes sampling, data collection , and analysis.

You can find out whether your procedures are unfeasible or susceptible to bias and make changes in time, but you can’t test a hypothesis with this type of study because it’s usually statistically underpowered .

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.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

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.

You can organise the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomisation can minimise the bias from order effects.

Questionnaires can be self-administered or researcher-administered.

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

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ENGL 103 E: Writing from Sources

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AI Index Report

Welcome to the seventh edition of the AI Index report. The 2024 Index is our most comprehensive to date and arrives at an important moment when AI’s influence on society has never been more pronounced. This year, we have broadened our scope to more extensively cover essential trends such as technical advancements in AI, public perceptions of the technology, and the geopolitical dynamics surrounding its development. Featuring more original data than ever before, this edition introduces new estimates on AI training costs, detailed analyses of the responsible AI landscape, and an entirely new chapter dedicated to AI’s impact on science and medicine.

Read the 2024 AI Index Report

The AI Index report tracks, collates, distills, and visualizes data related to artificial intelligence (AI). Our mission is to provide unbiased, rigorously vetted, broadly sourced data in order for policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI.

The AI Index is recognized globally as one of the most credible and authoritative sources for data and insights on artificial intelligence. Previous editions have been cited in major newspapers, including the The New York Times, Bloomberg, and The Guardian, have amassed hundreds of academic citations, and been referenced by high-level policymakers in the United States, the United Kingdom, and the European Union, among other places. This year’s edition surpasses all previous ones in size, scale, and scope, reflecting the growing significance that AI is coming to hold in all of our lives.

Steering Committee Co-Directors

Ray Perrault

Steering committee members.

Erik Brynjolfsson

John Etchemendy

Katrina Ligett

Terah Lyons

James Manyika

Juan Carlos Niebles

Vanessa Parli

Yoav Shoham

Russell Wald

Staff members.

Loredana Fattorini

Nestor Maslej

Letter from the co-directors.

A decade ago, the best AI systems in the world were unable to classify objects in images at a human level. AI struggled with language comprehension and could not solve math problems. Today, AI systems routinely exceed human performance on standard benchmarks.

Progress accelerated in 2023. New state-of-the-art systems like GPT-4, Gemini, and Claude 3 are impressively multimodal: They can generate fluent text in dozens of languages, process audio, and even explain memes. As AI has improved, it has increasingly forced its way into our lives. Companies are racing to build AI-based products, and AI is increasingly being used by the general public. But current AI technology still has significant problems. It cannot reliably deal with facts, perform complex reasoning, or explain its conclusions.

AI faces two interrelated futures. First, technology continues to improve and is increasingly used, having major consequences for productivity and employment. It can be put to both good and bad uses. In the second future, the adoption of AI is constrained by the limitations of the technology. Regardless of which future unfolds, governments are increasingly concerned. They are stepping in to encourage the upside, such as funding university R&D and incentivizing private investment. Governments are also aiming to manage the potential downsides, such as impacts on employment, privacy concerns, misinformation, and intellectual property rights.

As AI rapidly evolves, the AI Index aims to help the AI community, policymakers, business leaders, journalists, and the general public navigate this complex landscape. It provides ongoing, objective snapshots tracking several key areas: technical progress in AI capabilities, the community and investments driving AI development and deployment, public opinion on current and potential future impacts, and policy measures taken to stimulate AI innovation while managing its risks and challenges. By comprehensively monitoring the AI ecosystem, the Index serves as an important resource for understanding this transformative technological force.

On the technical front, this year’s AI Index reports that the number of new large language models released worldwide in 2023 doubled over the previous year. Two-thirds were open-source, but the highest-performing models came from industry players with closed systems. Gemini Ultra became the first LLM to reach human-level performance on the Massive Multitask Language Understanding (MMLU) benchmark; performance on the benchmark has improved by 15 percentage points since last year. Additionally, GPT-4 achieved an impressive 0.97 mean win rate score on the comprehensive Holistic Evaluation of Language Models (HELM) benchmark, which includes MMLU among other evaluations.

Although global private investment in AI decreased for the second consecutive year, investment in generative AI skyrocketed. More Fortune 500 earnings calls mentioned AI than ever before, and new studies show that AI tangibly boosts worker productivity. On the policymaking front, global mentions of AI in legislative proceedings have never been higher. U.S. regulators passed more AI-related regulations in 2023 than ever before. Still, many expressed concerns about AI’s ability to generate deepfakes and impact elections. The public became more aware of AI, and studies suggest that they responded with nervousness.

Ray Perrault Co-director, AI Index

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The Last Ta’ifa: Three Questions with Anthony H. Minnema

Tuesday, april 23, 2024.

In  The Last Ta’ifa: The Banu Hud and the Struggle for Political Legitimacy in al-Andalu s , Anthony H. Minnema shows how the Banu Hud, an Arab dynasty from Zaragoza, created and recreated their vision of an autonomous city-state ( ta’ifa ) in ways that reveal changes to legitimating strategies in al-Andalus and across the Mediterranean. In 1110, the Banu Hud lost control of their emirate in the north of Iberia and entered exile, ending their century-long rule. In this Three Questions blog, Minnema answers our questions about writing his book.

1. What is your favorite anecdote from your research for this book?

I find the figure of Sayf al-Dawla so compelling. He’s an exiled prince who bides his time in the service of a Christian king until he can strike out on his own and get revenge on the empire who orchestrated his family’s ouster from power in Zaragoza. However, once he becomes a ruler in Murcia, he had to choose between his former life as a vassal to a Christian king and a new life as an independent emir who must resist the forces of that same Christian king. There are no good options, and his actions resist any easy recourse to idealism or pragmatism. His choice and its consequences highlight the constructed nature of legitimacy in al-Andalus.

2. What do you wish you had known when you started writing your book that you know now?

I was not prepared for the nationalistic interpretations of the Banū Hūd and other ṭāʾifa leaders in general. I was prepared for the interpretations that viewed them as petty warlords bent on revenge or as pawns in a wider political game. I did not expect to see these figures described as proto-nationalists who resisted “African” rule and influence, which persists in some corners of Spain today.

3. How do you wish you could change your field?

I look forward to more source criticism on Arabic chronicles. My work on the concept of a ṭāʾifa illustrates how Muslim historians constantly rehashed previous critiques of Andalusi leaders. This posed a clear interpretative problem because the scholarly opinion did not match reality: if the leadership of figures like the Banū Hūd was so patently bad, why did they gain so much support from elite and the populace over the course of centuries? While I saw several scholars hint at the reasons for such negative portrayals, my book is the one of the few to challenge these assumptions about this appraisal of the ṭāʾifas and their leadership.

Anthony H. Minnema is Associate Professor of History at Samford University. His research focuses on premodern European and Middle Eastern history and on Muslim-Christian relations in the Middle Ages.

ORIGINAL RESEARCH article

Online poetry writing at school – comparing lower secondary students’ experiences between individual and collaborative poetry writing provisionally accepted.

• 1 University of Helsinki, Finland

The final, formatted version of the article will be published soon.

This study investigates how seventh-grade students experience online collaborative writing, its support in writing poems, and how collaboratively and individually written poems differ. The educational design research method was used in this mixed-methods study, which was conducted in natural classroom settings to investigate students' individual and collaborative poetry writing. The quantitative analysis of questionnaires and qualitative thematic analysis of post-experimental interviews show that the students enjoyed collaborative writing more and found it more accessible than individual writing. They experienced that it supported them in writing better poems and increased their writing confidence. They also appreciated the support of teamwork, although individual writing gave them more liberty to explore various aspects of poetry and express their feelings. From a pedagogical point of view, the students need to be provided with opportunities for collaborative poetry writing to make the writing process easier and more enjoyable. Online collaborative writing supports the process of poetry writing.

Keywords: Digital tool, technology in education, online poetry writing, collaborative writing Online Poetry Writing at School -Comparing Lower Secondary Students' Experiences between Individual and Collaborative Poetry Writing, poetry writing

Received: 02 Feb 2024; Accepted: 22 Apr 2024.

Copyright: © 2024 Kangasharju, Ilomäki and Toom. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mx. Arja Kangasharju, University of Helsinki, Helsinki, Finland

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Our changing climate is dramatically altering the landscape for mosquito-borne diseases, but other changes to the physical environment - like the proliferation of plastic trash - also make an impact, as mosquitos can breed in the plastic waste we discard. 

Since this study published, HERI-Kenya , a nonprofit started by Stanford infectious disease physician Desiree LaBeaud , has launched HERI Hub , a brick and mortar education hub that educates, empowers and inspires community members to improve the local environment to promote health.

Using plastic waste to build roads, buildings, and more

Stanford engineers  Michael Lepech  and  Zhiye Li  have a unique vision of the future: buildings and roads made from plastic waste. In this story, they discuss obstacles, opportunities, and other aspects of transforming or upcycling plastic waste into valuable materials. 

Since this white paper was published, students in Lepech's  life cycle assessment course  have explored the environmental and economic impacts of waste management, emissions, and energy efficiency of building materials for the San Francisco Museum of Modern Arts. In addition to recycled plastic, they proposed a photovoltaic system and conducted comparison studies to maximize the system’s life cycle. This work is being translated into an upcoming publication.

Stanford researchers show that mealworms can safely consume toxic additive-containing plastic

Mealworms are not only able to eat various forms of plastic, as previous research has shown, they can also consume potentially toxic plastic additives in polystyrene with no ill effects. The worms can then be used as a safe, protein-rich feed supplement.

Since this study published, it has inspired students across the world to learn about and experiment with mealworms and plastic waste. Stanford researchers involved with this and related studies have been inundated with requests for more information and guidance from people inspired by the potential solution.

Grants tackle the plastics problem

Stanford Woods Institute has awarded more than $23 million in funding to research projects that seek to identify solutions to pressing environment and sustainability challenges, including new approaches to plastic waste management. 

Converting polyethylene into palm oil

This project is developing a new technology to convert polyethylene — by far the most discarded plastic — into palm oil. The approach could add value to the plastic waste management chain while sourcing palm oil through a less destructive route.

Improving plastic waste management

This project aims to radically change the way plastic waste is processed via a new biotechnology paradigm: engineering highly active enzymes and microbes capable of breaking down polyesters in a decentralized network of “living” waste receptacles. 

More stories from Stanford

Eight simple but meaningful things you can do for the environment.

A new, artistic perspective on plastic waste

Whales eat colossal amounts of microplastics

Event | Pollution and Health

A greener future begins with small steps

Mosquito diseases on the move

Last straw: The path to reducing plastic pollution

Plastic ingestion by fish a growing problem

Stanford infectious disease expert Desiree LaBeaud talks trash, literally, on Stanford Engineering's The Future of Everything podcast. 

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Writing Survey Questions

Perhaps the most important part of the survey process is the creation of questions that accurately measure the opinions, experiences and behaviors of the public. Accurate random sampling will be wasted if the information gathered is built on a shaky foundation of ambiguous or biased questions. Creating good measures involves both writing good questions and organizing them to form the questionnaire.

Questionnaire design is a multistage process that requires attention to many details at once. Designing the questionnaire is complicated because surveys can ask about topics in varying degrees of detail, questions can be asked in different ways, and questions asked earlier in a survey may influence how people respond to later questions. Researchers are also often interested in measuring change over time and therefore must be attentive to how opinions or behaviors have been measured in prior surveys.

Surveyors may conduct pilot tests or focus groups in the early stages of questionnaire development in order to better understand how people think about an issue or comprehend a question. Pretesting a survey is an essential step in the questionnaire design process to evaluate how people respond to the overall questionnaire and specific questions, especially when questions are being introduced for the first time.

For many years, surveyors approached questionnaire design as an art, but substantial research over the past forty years has demonstrated that there is a lot of science involved in crafting a good survey questionnaire. Here, we discuss the pitfalls and best practices of designing questionnaires.

Question development

There are several steps involved in developing a survey questionnaire. The first is identifying what topics will be covered in the survey. For Pew Research Center surveys, this involves thinking about what is happening in our nation and the world and what will be relevant to the public, policymakers and the media. We also track opinion on a variety of issues over time so we often ensure that we update these trends on a regular basis to better understand whether people’s opinions are changing.

At Pew Research Center, questionnaire development is a collaborative and iterative process where staff meet to discuss drafts of the questionnaire several times over the course of its development. We frequently test new survey questions ahead of time through qualitative research methods such as  focus groups , cognitive interviews, pretesting (often using an  online, opt-in sample ), or a combination of these approaches. Researchers use insights from this testing to refine questions before they are asked in a production survey, such as on the ATP.

Measuring change over time

Many surveyors want to track changes over time in people’s attitudes, opinions and behaviors. To measure change, questions are asked at two or more points in time. A cross-sectional design surveys different people in the same population at multiple points in time. A panel, such as the ATP, surveys the same people over time. However, it is common for the set of people in survey panels to change over time as new panelists are added and some prior panelists drop out. Many of the questions in Pew Research Center surveys have been asked in prior polls. Asking the same questions at different points in time allows us to report on changes in the overall views of the general public (or a subset of the public, such as registered voters, men or Black Americans), or what we call “trending the data”.

When measuring change over time, it is important to use the same question wording and to be sensitive to where the question is asked in the questionnaire to maintain a similar context as when the question was asked previously (see  question wording  and  question order  for further information). All of our survey reports include a topline questionnaire that provides the exact question wording and sequencing, along with results from the current survey and previous surveys in which we asked the question.

The Center’s transition from conducting U.S. surveys by live telephone interviewing to an online panel (around 2014 to 2020) complicated some opinion trends, but not others. Opinion trends that ask about sensitive topics (e.g., personal finances or attending religious services ) or that elicited volunteered answers (e.g., “neither” or “don’t know”) over the phone tended to show larger differences than other trends when shifting from phone polls to the online ATP. The Center adopted several strategies for coping with changes to data trends that may be related to this change in methodology. If there is evidence suggesting that a change in a trend stems from switching from phone to online measurement, Center reports flag that possibility for readers to try to head off confusion or erroneous conclusions.

Open- and closed-ended questions

One of the most significant decisions that can affect how people answer questions is whether the question is posed as an open-ended question, where respondents provide a response in their own words, or a closed-ended question, where they are asked to choose from a list of answer choices.

For example, in a poll conducted after the 2008 presidential election, people responded very differently to two versions of the question: “What one issue mattered most to you in deciding how you voted for president?” One was closed-ended and the other open-ended. In the closed-ended version, respondents were provided five options and could volunteer an option not on the list.

When explicitly offered the economy as a response, more than half of respondents (58%) chose this answer; only 35% of those who responded to the open-ended version volunteered the economy. Moreover, among those asked the closed-ended version, fewer than one-in-ten (8%) provided a response other than the five they were read. By contrast, fully 43% of those asked the open-ended version provided a response not listed in the closed-ended version of the question. All of the other issues were chosen at least slightly more often when explicitly offered in the closed-ended version than in the open-ended version. (Also see  “High Marks for the Campaign, a High Bar for Obama”  for more information.)

Researchers will sometimes conduct a pilot study using open-ended questions to discover which answers are most common. They will then develop closed-ended questions based off that pilot study that include the most common responses as answer choices. In this way, the questions may better reflect what the public is thinking, how they view a particular issue, or bring certain issues to light that the researchers may not have been aware of.

When asking closed-ended questions, the choice of options provided, how each option is described, the number of response options offered, and the order in which options are read can all influence how people respond. One example of the impact of how categories are defined can be found in a Pew Research Center poll conducted in January 2002. When half of the sample was asked whether it was “more important for President Bush to focus on domestic policy or foreign policy,” 52% chose domestic policy while only 34% said foreign policy. When the category “foreign policy” was narrowed to a specific aspect – “the war on terrorism” – far more people chose it; only 33% chose domestic policy while 52% chose the war on terrorism.

In most circumstances, the number of answer choices should be kept to a relatively small number – just four or perhaps five at most – especially in telephone surveys. Psychological research indicates that people have a hard time keeping more than this number of choices in mind at one time. When the question is asking about an objective fact and/or demographics, such as the religious affiliation of the respondent, more categories can be used. In fact, they are encouraged to ensure inclusivity. For example, Pew Research Center’s standard religion questions include more than 12 different categories, beginning with the most common affiliations (Protestant and Catholic). Most respondents have no trouble with this question because they can expect to see their religious group within that list in a self-administered survey.

In addition to the number and choice of response options offered, the order of answer categories can influence how people respond to closed-ended questions. Research suggests that in telephone surveys respondents more frequently choose items heard later in a list (a “recency effect”), and in self-administered surveys, they tend to choose items at the top of the list (a “primacy” effect).

Because of concerns about the effects of category order on responses to closed-ended questions, many sets of response options in Pew Research Center’s surveys are programmed to be randomized to ensure that the options are not asked in the same order for each respondent. Rotating or randomizing means that questions or items in a list are not asked in the same order to each respondent. Answers to questions are sometimes affected by questions that precede them. By presenting questions in a different order to each respondent, we ensure that each question gets asked in the same context as every other question the same number of times (e.g., first, last or any position in between). This does not eliminate the potential impact of previous questions on the current question, but it does ensure that this bias is spread randomly across all of the questions or items in the list. For instance, in the example discussed above about what issue mattered most in people’s vote, the order of the five issues in the closed-ended version of the question was randomized so that no one issue appeared early or late in the list for all respondents. Randomization of response items does not eliminate order effects, but it does ensure that this type of bias is spread randomly.

Questions with ordinal response categories – those with an underlying order (e.g., excellent, good, only fair, poor OR very favorable, mostly favorable, mostly unfavorable, very unfavorable) – are generally not randomized because the order of the categories conveys important information to help respondents answer the question. Generally, these types of scales should be presented in order so respondents can easily place their responses along the continuum, but the order can be reversed for some respondents. For example, in one of Pew Research Center’s questions about abortion, half of the sample is asked whether abortion should be “legal in all cases, legal in most cases, illegal in most cases, illegal in all cases,” while the other half of the sample is asked the same question with the response categories read in reverse order, starting with “illegal in all cases.” Again, reversing the order does not eliminate the recency effect but distributes it randomly across the population.

Question wording

The choice of words and phrases in a question is critical in expressing the meaning and intent of the question to the respondent and ensuring that all respondents interpret the question the same way. Even small wording differences can substantially affect the answers people provide.

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An example of a wording difference that had a significant impact on responses comes from a January 2003 Pew Research Center survey. When people were asked whether they would “favor or oppose taking military action in Iraq to end Saddam Hussein’s rule,” 68% said they favored military action while 25% said they opposed military action. However, when asked whether they would “favor or oppose taking military action in Iraq to end Saddam Hussein’s rule  even if it meant that U.S. forces might suffer thousands of casualties, ” responses were dramatically different; only 43% said they favored military action, while 48% said they opposed it. The introduction of U.S. casualties altered the context of the question and influenced whether people favored or opposed military action in Iraq.

There has been a substantial amount of research to gauge the impact of different ways of asking questions and how to minimize differences in the way respondents interpret what is being asked. The issues related to question wording are more numerous than can be treated adequately in this short space, but below are a few of the important things to consider:

First, it is important to ask questions that are clear and specific and that each respondent will be able to answer. If a question is open-ended, it should be evident to respondents that they can answer in their own words and what type of response they should provide (an issue or problem, a month, number of days, etc.). Closed-ended questions should include all reasonable responses (i.e., the list of options is exhaustive) and the response categories should not overlap (i.e., response options should be mutually exclusive). Further, it is important to discern when it is best to use forced-choice close-ended questions (often denoted with a radio button in online surveys) versus “select-all-that-apply” lists (or check-all boxes). A 2019 Center study found that forced-choice questions tend to yield more accurate responses, especially for sensitive questions.  Based on that research, the Center generally avoids using select-all-that-apply questions.

It is also important to ask only one question at a time. Questions that ask respondents to evaluate more than one concept (known as double-barreled questions) – such as “How much confidence do you have in President Obama to handle domestic and foreign policy?” – are difficult for respondents to answer and often lead to responses that are difficult to interpret. In this example, it would be more effective to ask two separate questions, one about domestic policy and another about foreign policy.

In general, questions that use simple and concrete language are more easily understood by respondents. It is especially important to consider the education level of the survey population when thinking about how easy it will be for respondents to interpret and answer a question. Double negatives (e.g., do you favor or oppose  not  allowing gays and lesbians to legally marry) or unfamiliar abbreviations or jargon (e.g., ANWR instead of Arctic National Wildlife Refuge) can result in respondent confusion and should be avoided.

Similarly, it is important to consider whether certain words may be viewed as biased or potentially offensive to some respondents, as well as the emotional reaction that some words may provoke. For example, in a 2005 Pew Research Center survey, 51% of respondents said they favored “making it legal for doctors to give terminally ill patients the means to end their lives,” but only 44% said they favored “making it legal for doctors to assist terminally ill patients in committing suicide.” Although both versions of the question are asking about the same thing, the reaction of respondents was different. In another example, respondents have reacted differently to questions using the word “welfare” as opposed to the more generic “assistance to the poor.” Several experiments have shown that there is much greater public support for expanding “assistance to the poor” than for expanding “welfare.”

We often write two versions of a question and ask half of the survey sample one version of the question and the other half the second version. Thus, we say we have two  forms  of the questionnaire. Respondents are assigned randomly to receive either form, so we can assume that the two groups of respondents are essentially identical. On questions where two versions are used, significant differences in the answers between the two forms tell us that the difference is a result of the way we worded the two versions.

One of the most common formats used in survey questions is the “agree-disagree” format. In this type of question, respondents are asked whether they agree or disagree with a particular statement. Research has shown that, compared with the better educated and better informed, less educated and less informed respondents have a greater tendency to agree with such statements. This is sometimes called an “acquiescence bias” (since some kinds of respondents are more likely to acquiesce to the assertion than are others). This behavior is even more pronounced when there’s an interviewer present, rather than when the survey is self-administered. A better practice is to offer respondents a choice between alternative statements. A Pew Research Center experiment with one of its routinely asked values questions illustrates the difference that question format can make. Not only does the forced choice format yield a very different result overall from the agree-disagree format, but the pattern of answers between respondents with more or less formal education also tends to be very different.

One other challenge in developing questionnaires is what is called “social desirability bias.” People have a natural tendency to want to be accepted and liked, and this may lead people to provide inaccurate answers to questions that deal with sensitive subjects. Research has shown that respondents understate alcohol and drug use, tax evasion and racial bias. They also may overstate church attendance, charitable contributions and the likelihood that they will vote in an election. Researchers attempt to account for this potential bias in crafting questions about these topics. For instance, when Pew Research Center surveys ask about past voting behavior, it is important to note that circumstances may have prevented the respondent from voting: “In the 2012 presidential election between Barack Obama and Mitt Romney, did things come up that kept you from voting, or did you happen to vote?” The choice of response options can also make it easier for people to be honest. For example, a question about church attendance might include three of six response options that indicate infrequent attendance. Research has also shown that social desirability bias can be greater when an interviewer is present (e.g., telephone and face-to-face surveys) than when respondents complete the survey themselves (e.g., paper and web surveys).

Lastly, because slight modifications in question wording can affect responses, identical question wording should be used when the intention is to compare results to those from earlier surveys. Similarly, because question wording and responses can vary based on the mode used to survey respondents, researchers should carefully evaluate the likely effects on trend measurements if a different survey mode will be used to assess change in opinion over time.

Question order

Once the survey questions are developed, particular attention should be paid to how they are ordered in the questionnaire. Surveyors must be attentive to how questions early in a questionnaire may have unintended effects on how respondents answer subsequent questions. Researchers have demonstrated that the order in which questions are asked can influence how people respond; earlier questions can unintentionally provide context for the questions that follow (these effects are called “order effects”).

One kind of order effect can be seen in responses to open-ended questions. Pew Research Center surveys generally ask open-ended questions about national problems, opinions about leaders and similar topics near the beginning of the questionnaire. If closed-ended questions that relate to the topic are placed before the open-ended question, respondents are much more likely to mention concepts or considerations raised in those earlier questions when responding to the open-ended question.

For closed-ended opinion questions, there are two main types of order effects: contrast effects ( where the order results in greater differences in responses), and assimilation effects (where responses are more similar as a result of their order).

An example of a contrast effect can be seen in a Pew Research Center poll conducted in October 2003, a dozen years before same-sex marriage was legalized in the U.S. That poll found that people were more likely to favor allowing gays and lesbians to enter into legal agreements that give them the same rights as married couples when this question was asked after one about whether they favored or opposed allowing gays and lesbians to marry (45% favored legal agreements when asked after the marriage question, but 37% favored legal agreements without the immediate preceding context of a question about same-sex marriage). Responses to the question about same-sex marriage, meanwhile, were not significantly affected by its placement before or after the legal agreements question.

Another experiment embedded in a December 2008 Pew Research Center poll also resulted in a contrast effect. When people were asked “All in all, are you satisfied or dissatisfied with the way things are going in this country today?” immediately after having been asked “Do you approve or disapprove of the way George W. Bush is handling his job as president?”; 88% said they were dissatisfied, compared with only 78% without the context of the prior question.

Responses to presidential approval remained relatively unchanged whether national satisfaction was asked before or after it. A similar finding occurred in December 2004 when both satisfaction and presidential approval were much higher (57% were dissatisfied when Bush approval was asked first vs. 51% when general satisfaction was asked first).

Several studies also have shown that asking a more specific question before a more general question (e.g., asking about happiness with one’s marriage before asking about one’s overall happiness) can result in a contrast effect. Although some exceptions have been found, people tend to avoid redundancy by excluding the more specific question from the general rating.

Assimilation effects occur when responses to two questions are more consistent or closer together because of their placement in the questionnaire. We found an example of an assimilation effect in a Pew Research Center poll conducted in November 2008 when we asked whether Republican leaders should work with Obama or stand up to him on important issues and whether Democratic leaders should work with Republican leaders or stand up to them on important issues. People were more likely to say that Republican leaders should work with Obama when the question was preceded by the one asking what Democratic leaders should do in working with Republican leaders (81% vs. 66%). However, when people were first asked about Republican leaders working with Obama, fewer said that Democratic leaders should work with Republican leaders (71% vs. 82%).

The order questions are asked is of particular importance when tracking trends over time. As a result, care should be taken to ensure that the context is similar each time a question is asked. Modifying the context of the question could call into question any observed changes over time (see  measuring change over time  for more information).

A questionnaire, like a conversation, should be grouped by topic and unfold in a logical order. It is often helpful to begin the survey with simple questions that respondents will find interesting and engaging. Throughout the survey, an effort should be made to keep the survey interesting and not overburden respondents with several difficult questions right after one another. Demographic questions such as income, education or age should not be asked near the beginning of a survey unless they are needed to determine eligibility for the survey or for routing respondents through particular sections of the questionnaire. Even then, it is best to precede such items with more interesting and engaging questions. One virtue of survey panels like the ATP is that demographic questions usually only need to be asked once a year, not in each survey.

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