thesis study questionnaire

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!

Related articles.

Online Panels: What They Are & How to Use Them Effectively

The Complete Guide to Survey Logic (+Expert Tips)

Focus Group vs. Survey: Which One Should You Use?

Leading Questions: What They Are & Why They Matter [+ Examples]

What are Survey Sample Sizes & How to Find Your Sample Size

24 Diversity, Equity, and Inclusion Survey Questions to Ask Your Employees

How Long Should a Survey Be? The Ideal Survey Length [New Data]

What Is Survey Fatigue & How to Avoid It [Research]

Common Types of Survey Bias and How to Avoid Them

SurveyMonkey vs. Qualtrics: What’s the Difference?

5 free templates for learning more about your customers and respondents.

Survey Questionnaire Development

Survey questionnaire are generally used for research purposes to obtain data from the public or to determine the distribution of certain characteristics in a population. Formulating a survey questionnaire is one of the most vital stages in the process of survey development. Most of the components in a survey are based on common sense, but there are certain aspects that the authors should be aware of. We believe in providing numerous samples, surveys, questions and responses that will help you in constructing the survey questionnaires.

Some of the ground rules to be kept in mind before writing the first word:

• Each of the questions should directly associate to the objectives of the survey questionnaire.
• Each and every respondent should be able to answer all questions with ease
• Each question should be formed in a way that all respondents interpret it in the same manner
• Each question should give answers to what you need to know, not what would be preferable to know

The following are the four main parts of a survey questionnaire. Though each of these parts is different from each other, it is important to understand that all of them are necessary for drafting a good survey questionnaire .

There are four main parts to a survey questionnaire. Though each of them is different from each other, it is significant to know that all of them play a vital role in formulating a good questionnaire.

The four main parts of a survey questionnaire development are invitation, introduction, question types and close. There are various ways as to how these surveys can be used such as emails, website links, online advertising etc. The five main parts of the invitation are introduction, why are only certain respondents selected to answer the questionnaire, how long the questionnaire will usually take, what are the benefits they will get for answering the questionnaire and how their responses will be used by the surveyors or researchers.

The introduction part of the survey questionnaire will include an attractive introduction and that clearly portrays the aim of the research.

There are five steps in writing a survey questionnaire such as determining the aim, finalizing the attributes to gauge, recognize the type of audience, select the scales of measurement and finally check the reliability and the validity of the survey.

After formulating a survey questionnaire, it is essential to check for errors because they fail to attain their goals due to the errors. Random errors are responsible for the decreased reliability of a survey and it happens when questions are poorly structured or presented in an inaccurate way.

24/7 Support - Order Now

Read our research on: Israel | Internet & Technology | Science

Regions & Countries

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.

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.

U.S. Surveys

Other research methods.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

Call us : 0091 80 4111 6961

• Questionnaire Design

Why Seek Professional Help for Questionnaire Development

A questionnaire is a standardised data collection tool which can be used to address questions to the research samples across subject domains. We, at PhD Thesis aim at designing questionnaires that can minimise any type of bias or error, increase response rates, and enhance analysis. Carefully curated questionnaires can result in improved decision making and concluding of extensive research works. We have dedicated PhD thesis questionnaire design services in Bangalore for PhD research to design various data collection tools, including questionnaires, surveys and interview guides. Whether you are conducting quantitative or qualitative research, our team follows the prescribed formats and caters to the specific research objectives and aims. We ensure that the questionnaires so designed are reliable, valid and universally acceptable.

Multiple Aspects of Our Questionnaire designed

• 1. Target audience oriented
• 2. Caters to all research objectives
• 3. Comprehensible language for easy understanding Improving
• 4. Sequential ordering/layout of questions for higher response rate
• 5. Format compatible with data analysis software to be used

What is included in PhD questionnaire designing service?

Extracting relevant information.

We make sure that the questionnaire is developed with an aim to elicit only the relevant information per your study objectives from samples. This enables you to find usable data without having to exhaust through large amounts of information. We ensure that all research questions will be catered to through the different sections under the questionnaire.

Precision to achieve study goals

Our experts offering PhD thesis questionnaire design services in Bangalore carefully understand the goals and design of your study in order to design the best data collection tool intended to gather accurate data.

Open- and close-ended questions

We help you in designing both open-ended and closed-ended questions. This depends on the way you want to capture your data for your specific research. It may also depend on your study type, whether it is qualitative, quantitative, or mixed design research.

Questions for easy interpretation

Further, we ensure that your questionnaire is designed with such questions that can make it easier for you to later analyse and interpret the responses received. For this purpose, we word them carefully and offer clear instructions to the respondents.

Ethical questionnaire design

Questions included in a study questionnaire take into account the target respondents’ sentiments, socio-economic backgrounds and avoid any trigger points or double-meaning questions resulting in biased or unreliable data collection.

Making the questionnaire flawless

After your questionnaire is designed, we check it for the accuracy of language and format. We clear it of every single error, whether it be of grammar or format. We also apply the apt rating scale, checklist, or similar response options to enable participants to convey their response clearly.

Reliability and validity testing

We apply the developed questionnaire on a small sample to test its reliability and validity. It is very important that your study tool is reliable when used repeatedly under the same conditions. It has to be a standardised tool of study.

Gain an Edge with an Effective Data Collection Tool

Our statistical experts have an intensive knowledge of several ratings scales, question types, ethical issues, reliability and validity factors, etc. Thus, they are able to provide an objective set of enquiries in the form of a questionnaire. Designing a questionnaire is not simply taking some raw data and converting it into usable information. It demands detailed knowledge of a wide range of statistical methods and techniques, as well as research methods to be able to design a wonderful surveying tool.

As our statistical experts possess the experience of developing a variety of data collection tools for PhD candidates working in varied academic domains, they are skilled to handle every minor aspect of developing a study questionnaire for you. To know more about our questionnaire design services for PhD research, send us an enquiry email at [email protected] .

Request a Call Back

Latest posts from our blog.

• Limitations and Delimitations: The Boundaries and Weakness of Your Research
• Developing Your Conference Paper with PhD Thesis
• Evolution of the Problem Statement: From Arriving at it to Solidification
• Understanding Quasi-Experimental Quantitative Research Design
• Chaptering Your Research Paper: Writing the Discussion Section
• 5 Unknown Differences Between Limitation and Delimitation
• 3 Game-Changing Tips for PhD Thesis Writing in 2023-24
• What to Do When PhD Dissertation Defense Preparation Derail?
• Common Pitfalls in Avoiding Rejection for PhD Thesis
• Unravelling the Pros and Cons of Research Paper Writing Help for PhD
• Effective Data Presentation and Analysis in Research Paper Writing in PhD For Publication In International Journals
• A fresh insight into ethnographic research design processes
• Ways to Explore and Address Research Gaps in Digital Marketing: A PhD Researchers’ Guide
• Solving the statistical juggle: Anova, Ancova,Manova, Mancova
• How to Select a questionnaire method based on your research topics ?

Need more details? Contact us

We are here to assist you. Contact us by phone, email.

How to get published in SCI Indexed Journals

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Chapter 9: Survey Research

Constructing Survey Questionnaires

Learning Objectives

• Describe the cognitive processes involved in responding to a survey item.
• Explain what a context effect is and give some examples.
• Create a simple survey questionnaire based on principles of effective item writing and organization.

The heart of any survey research project is the survey questionnaire itself. Although it is easy to think of interesting questions to ask people, constructing a good survey questionnaire is not easy at all. The problem is that the answers people give can be influenced in unintended ways by the wording of the items, the order of the items, the response options provided, and many other factors. At best, these influences add noise to the data. At worst, they result in systematic biases and misleading results. In this section, therefore, we consider some principles for constructing survey questionnaires to minimize these unintended effects and thereby maximize the reliability and validity of respondents’ answers.

Survey Responding as a Psychological Process

Before looking at specific principles of survey questionnaire construction, it will help to consider survey responding as a psychological process.

A Cognitive Model

Figure 9.1  presents a model of the cognitive processes that people engage in when responding to a survey item (Sudman, Bradburn, & Schwarz, 1996) [1] . Respondents must interpret the question, retrieve relevant information from memory, form a tentative judgment, convert the tentative judgment into one of the response options provided (e.g., a rating on a 1-to-7 scale), and finally edit their response as necessary.

Consider, for example, the following questionnaire item:

How many alcoholic drinks do you consume in a typical day?

• _____ a lot more than average
• _____ somewhat more than average
• _____ average
• _____ somewhat fewer than average
• _____ a lot fewer than average

Although this item at first seems straightforward, it poses several difficulties for respondents. First, they must interpret the question. For example, they must decide whether “alcoholic drinks” include beer and wine (as opposed to just hard liquor) and whether a “typical day” is a typical weekday, typical weekend day, or both . Even though Chang and Krosnick (2003) [2] found that asking about “typical” behaviour has been shown to be more valid than asking about “past” behaviour, their study compared “typical week” to “past week” and may be different when considering typical weekdays or weekend days) . Once they have interpreted the question, they must retrieve relevant information from memory to answer it. But what information should they retrieve, and how should they go about retrieving it? They might think vaguely about some recent occasions on which they drank alcohol, they might carefully try to recall and count the number of alcoholic drinks they consumed last week, or they might retrieve some existing beliefs that they have about themselves (e.g., “I am not much of a drinker”). Then they must use this information to arrive at a tentative judgment about how many alcoholic drinks they consume in a typical day. For example, this  mental calculation  might mean dividing the number of alcoholic drinks they consumed last week by seven to come up with an average number per day. Then they must format this tentative answer in terms of the response options actually provided. In this case, the options pose additional problems of interpretation. For example, what does “average” mean, and what would count as “somewhat more” than average? Finally, they must decide whether they want to report the response they have come up with or whether they want to edit it in some way. For example, if they believe that they drink much more than average, they might not want to report th e higher number  for fear of looking bad in the eyes of the researcher.

From this perspective, what at first appears to be a simple matter of asking people how much they drink (and receiving a straightforward answer from them) turns out to be much more complex.

Context Effects on Questionnaire Responses

Again, this complexity can lead to unintended influences on respondents’ answers. These are often referred to as  context effects  because they are not related to the content of the item but to the context in which the item appears (Schwarz & Strack, 1990) [3] . For example, there is an  item-order effect  when the order in which the items are presented affects people’s responses. One item can change how participants interpret a later item or change the information that they retrieve to respond to later items. For example, researcher Fritz Strack and his colleagues asked college students about both their general life satisfaction and their dating frequency (Strack, Martin, & Schwarz, 1988) [4] . When the life satisfaction item came first, the correlation between the two was only −.12, suggesting that the two variables are only weakly related. But when the dating frequency item came first, the correlation between the two was +.66, suggesting that those who date more have a strong tendency to be more satisfied with their lives. Reporting the dating frequency first made that information more accessible in memory so that they were more likely to base their life satisfaction rating on it.

The response options provided can also have unintended effects on people’s responses (Schwarz, 1999) [5] . For example, when people are asked how often they are “really irritated” and given response options ranging from “less than once a year” to “more than once a month,” they tend to think of major irritations and report being irritated infrequently. But when they are given response options ranging from “less than once a day” to “several times a month,” they tend to think of minor irritations and report being irritated frequently. People also tend to assume that middle response options represent what is normal or typical. So if they think of themselves as normal or typical, they tend to choose middle response options. For example, people are likely to report watching more television when the response options are centred on a middle option of 4 hours than when centred on a middle option of 2 hours.  To mitigate against order effects, rotate questions and response items when there is no natural order. Counterbalancing is a good practice for survey questions and can reduce response order effects which show that among undecided voters, the first candidate listed in a ballot receives a 2.5% boost simply by virtue of being listed first [6] !

Writing Survey Questionnaire Items

Types of items.

Questionnaire items can be either open-ended or closed-ended.  Open-ended items  simply ask a question and allow participants to answer in whatever way they choose. The following are examples of open-ended questionnaire items.

• “What is the most important thing to teach children to prepare them for life?”
• “Please describe a time when you were discriminated against because of your age.”
• “Is there anything else you would like to tell us about?”

Open-ended items are useful when researchers do not know how participants might respond or want to avoid influencing their responses. They tend to be used when researchers have more vaguely defined research questions—often in the early stages of a research project. Open-ended items are relatively easy to write because there are no response options to worry about. However, they take more time and effort on the part of participants, and they are more difficult for the researcher to analy z e because the answers must be transcribed, coded, and submitted to some form of qualitative analysis, such as content analysis.  The advantage to open-ended items is that they are unbiased and do not provide respondents with expectations of what the researcher might be looking for. Open-ended items are also more valid and more reliable. The disadvantage is that respondents are more likely to skip open-ended items because they take longer to answer. It is best to use open-ended questions when the answer is unsure and for quantities which can easily be converted to categories later in the analysis.

Closed-ended items  ask a question and provide a set of response options for participants to choose from. The alcohol item just mentioned is an example, as are the following:

  How old are you?

• _____ Under 18
• _____ 18 to 34
• _____ 35 to 49
• _____ 50 to 70
• _____ Over 70

On a scale of 0 (no pain at all) to 10 (worst pain ever experienced), how much pain are you in right now?

Have you ever in your adult life been depressed for a period of 2 weeks or more?

Closed-ended items are used when researchers have a good idea of the different responses that participants might make. They are also used when researchers are interested in a well-defined variable or construct such as participants’ level of agreement with some statement, perceptions of risk, or frequency of a particular behaviour. Closed-ended items are more difficult to write because they must include an appropriate set of response options. However, they are relatively quick and easy for participants to complete. They are also much easier for researchers to analyze because the responses can be easily converted to numbers and entered into a spreadsheet. For these reasons, closed-ended items are much more common.

All closed-ended items include a set of response options from which a participant must choose. For categorical variables like sex, race, or political party preference, the categories are usually listed and participants choose the one (or ones) that they belong to. For quantitative variables, a rating scale is typically provided. A  rating scale  is an ordered set of responses that participants must choose from.  Figure 9.2  shows several examples. The number of response options on a typical rating scale ranges from three to 11—although five and seven are probably most common. Five-point scales are best for unipolar scales where only one construct is tested, such as frequency (Never, Rarely, Sometimes, Often, Always). Seven-point scales are best for bipolar scales where there is a dichotomous spectrum, such as liking (Like very much, Like somewhat, Like slightly, Neither like nor dislike, Dislike slightly, Dislike somewhat, Dislike very much). For bipolar questions, it is useful to offer an earlier question that branches them into an area of the scale; if asking about liking ice cream, first ask “Do you generally like or dislike ice cream?” Once the respondent chooses like or dislike, refine it by offering them one of choices from the seven-point scale.  Branching improves both reliability and validity  (Krosnick & Berent, 1993) [7] .  Although you often see scales with numerical labels, it is best to only present verbal labels to the respondents but convert them to numerical values in the analyses. Avoid partial labels or length or overly specific labels. In some cases, the verbal labels can be supplemented with (or even replaced by) meaningful graphics. The last rating scale shown in  Figure 9.2  is a visual-analog scale, on which participants make a mark somewhere along the horizontal line to indicate the magnitude of their response.

What is a Likert Scale?

In reading about psychological research, you are likely to encounter the term  Likert scale . Although this term is sometimes used to refer to almost any rating scale (e.g., a 0-to-10 life satisfaction scale), it has a much more precise meaning.

In the 1930s, researcher Rensis Likert (pronounced LICK-ert) created a new approach for measuring people’s attitudes (Likert, 1932) [8] . It involves presenting people with several statements—including both favourable and unfavourable statements—about some person, group, or idea. Respondents then express their agreement or disagreement with each statement on a 5-point scale:  Strongly Agree ,  Agree ,  Neither Agree nor Disagree ,  Disagree , Strongly Disagree . Numbers are assigned to each response (with reverse coding as necessary) and then summed across all items to produce a score representing the attitude toward the person, group, or idea. The entire set of items came to be called a Likert scale.

Thus unless you are measuring people’s attitude toward something by assessing their level of agreement with several statements about it, it is best to avoid calling it a Likert scale. You are probably just using a “rating scale.”

Writing Effective Items

We can now consider some principles of writing questionnaire items that minimize unintended context effects and maximize the reliability and validity of participants’ responses. A rough guideline for writing questionnaire items is provided by the BRUSO model (Peterson, 2000) [9] . An acronym,  BRUSO  stands for “brief,” “relevant,” “unambiguous,” “specific,” and “objective.” Effective questionnaire items are  brief  and to the point. They avoid long, overly technical, or unnecessary words. This brevity makes them easier for respondents to understand and faster for them to complete. Effective questionnaire items are also  relevant  to the research question. If a respondent’s sexual orientation, marital status, or income is not relevant, then items on them should probably not be included. Again, this makes the questionnaire faster to complete, but it also avoids annoying respondents with what they will rightly perceive as irrelevant or even “nosy” questions. Effective questionnaire items are also unambiguous ; they can be interpreted in only one way. Part of the problem with the alcohol item presented earlier in this section is that different respondents might have different ideas about what constitutes “an alcoholic drink” or “a typical day.” Effective questionnaire items are also  specific ,  so that it is clear to respondents what their response  should  be about and clear to researchers what it  is  about. A common problem here is closed-ended items that are “double barrelled.” They ask about two conceptually separate issues but allow only one response. For example, “Please rate the extent to which you have been feeling anxious and depressed.” This item should probably be split into two separate items—one about anxiety and one about depression. Finally, effective questionnaire items are  objective  in the sense that they do not reveal the researcher’s own opinions or lead participants to answer in a particular way. Table 9.2  shows some examples of poor and effective questionnaire items based on the BRUSO criteria. The best way to know how people interpret the wording of the question is to conduct pre-tests and ask a few people to explain how they interpreted the question.

For closed-ended items, it is also important to create an appropriate response scale. For categorical variables, the categories presented should generally be mutually exclusive and exhaustive. Mutually exclusive categories do not overlap. For a religion item, for example, the categories of  Christian  and Catholic  are not mutually exclusive but  Protestant  and  Catholic are. Exhaustive categories cover all possible responses.

Although  Protestant  and  Catholic  are mutually exclusive, they are not exhaustive because there are many other religious categories that a respondent might select:  Jewish ,  Hindu ,  Buddhist , and so on. In many cases, it is not feasible to include every possible category, in which case an  Other  category, with a space for the respondent to fill in a more specific response, is a good solution. If respondents could belong to more than one category (e.g., race), they should be instructed to choose all categories that apply.

For rating scales, five or seven response options generally allow about as much precision as respondents are capable of. However, numerical scales with more options can sometimes be appropriate. For dimensions such as attractiveness, pain, and likelihood, a 0-to-10 scale will be familiar to many respondents and easy for them to use. Regardless of the number of response options, the most extreme ones should generally be “balanced” around a neutral or modal midpoint. An example of an unbalanced rating scale measuring perceived likelihood might look like this:

Unlikely  |  Somewhat Likely  |  Likely  |  Very Likely  |  Extremely Likely

A balanced version might look like this:

Extremely Unlikely  |  Somewhat Unlikely  |  As Likely as Not  |  Somewhat Likely  | Extremely Likely

 Note, however, that a middle or neutral response option does not have to be included. Researchers sometimes choose to leave it out because they want to encourage respondents to think more deeply about their response and not simply choose the middle option by default. Including middle alternatives on bipolar dimensions is useful to allow people to genuinely choose an option that is neither.

Formatting the Questionnaire

Writing effective items is only one part of constructing a survey questionnaire. For one thing, every survey questionnaire should have a written or spoken introduction that serves two basic functions (Peterson, 2000) [10] . One is to encourage respondents to participate in the survey. In many types of research, such encouragement is not necessary either because participants do not know they are in a study (as in naturalistic observation) or because they are part of a subject pool and have already shown their willingness to participate by signing up and showing up for the study. Survey research usually catches respondents by surprise when they answer their phone, go to their mailbox, or check their e-mail—and the researcher must make a good case for why they should agree to participate. Thus the introduction should briefly explain the purpose of the survey and its importance, provide information about the sponsor of the survey (university-based surveys tend to generate higher response rates), acknowledge the importance of the respondent’s participation, and describe any incentives for participating.

The second function of the introduction is to establish informed consent. Remember that this aim means describing to respondents everything that might affect their decision to participate. This includes the topics covered by the survey, the amount of time it is likely to take, the respondent’s option to withdraw at any time, confidentiality issues, and so on. Written consent forms are not typically used in survey research, so it is important that this part of the introduction be well documented and presented clearly and in its entirety to every respondent.

The introduction should be followed by the substantive questionnaire items. But first, it is important to present clear instructions for completing the questionnaire, including examples of how to use any unusual response scales. Remember that the introduction is the point at which respondents are usually most interested and least fatigued, so it is good practice to start with the most important items for purposes of the research and proceed to less important items. Items should also be grouped by topic or by type. For example, items using the same rating scale (e.g., a 5-point agreement scale) should be grouped together if possible to make things faster and easier for respondents. Demographic items are often presented last because they are least interesting to participants but also easy to answer in the event respondents have become tired or bored. Of course, any survey should end with an expression of appreciation to the respondent.

Key Takeaways

• Responding to a survey item is itself a complex cognitive process that involves interpreting the question, retrieving information, making a tentative judgment, putting that judgment into the required response format, and editing the response.
• Survey questionnaire responses are subject to numerous context effects due to question wording, item order, response options, and other factors. Researchers should be sensitive to such effects when constructing surveys and interpreting survey results.
• Survey questionnaire items are either open-ended or closed-ended. Open-ended items simply ask a question and allow respondents to answer in whatever way they want. Closed-ended items ask a question and provide several response options that respondents must choose from.
• Use verbal labels instead of numerical labels although the responses can be converted to numerical data in the analyses.
• According to the BRUSO model, questionnaire items should be brief, relevant, unambiguous, specific, and objective.
• Discussion: Write a survey item and then write a short description of how someone might respond to that item based on the cognitive model of survey responding (or choose any item on the Rosenberg Self-Esteem Scale .
• How much does the respondent use Facebook?
• How much exercise does the respondent get?
• How likely does the respondent think it is that the incumbent will be re-elected in the next presidential election?
• To what extent does the respondent experience “road rage”?

Long Descriptions

Figure 9.1 long description: Flowchart modelling the cognitive processes involved in responding to a survey item. In order, these processes are:

• Question Interpretation
• Information Retrieval
• Judgment Formation
• Response Formatting
• Response Editing

[Return to Figure 9.1]

Figure 9.2 long description: Three different rating scales for survey questions. The first scale provides a choice between “strongly agree,” “agree,” “neither agree nor disagree,” “disagree,” and “strongly disagree.” The second is a scale from 1 to 7, with 1 being “extremely unlikely” and 7 being “extremely likely.” The third is a sliding scale, with one end marked “extremely unfriendly” and the other “extremely friendly.” [Return to Figure 9.2]

Figure 9.3 long description: A note reads, “Dear Isaac. Do you like me?” with two check boxes reading “yes” or “no.” Someone has added a third check box, which they’ve checked, that reads, “There is as yet insufficient data for a meaningful answer.” [Return to Figure 9.3]

Media Attributions

• Study  by XKCD  CC BY-NC (Attribution NonCommercial)
• Sudman, S., Bradburn, N. M., & Schwarz, N. (1996). Thinking about answers: The application of cognitive processes to survey methodology . San Francisco, CA: Jossey-Bass. ↵
• Chang, L., & Krosnick, J.A. (2003). Measuring the frequency of regular behaviors: Comparing the ‘typical week’ to the ‘past week’. Sociological Methodology, 33 , 55-80. ↵
• Schwarz, N., & Strack, F. (1990). Context effects in attitude surveys: Applying cognitive theory to social research. In W. Stroebe & M. Hewstone (Eds.), European review of social psychology (Vol. 2, pp. 31–50). Chichester, UK: Wiley. ↵
• Strack, F., Martin, L. L., & Schwarz, N. (1988). Priming and communication: The social determinants of information use in judgments of life satisfaction. European Journal of Social Psychology, 18 , 429–442. ↵
• Schwarz, N. (1999). Self-reports: How the questions shape the answers. American Psychologist, 54 , 93–105. ↵
• Miller, J.M. & Krosnick, J.A. (1998). The impact of candidate name order on election outcomes. Public Opinion Quarterly, 62 (3), 291-330. ↵
• Krosnick, J.A. & Berent, M.K. (1993). Comparisons of party identification and policy preferences: The impact of survey question format. American Journal of Political Science, 27 (3), 941-964. ↵
• Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology,140 , 1–55. ↵
• Peterson, R. A. (2000). Constructing effective questionnaires . Thousand Oaks, CA: Sage. ↵

Being tested in one condition can also change how participants perceive stimuli or interpret their task in later conditions.

The order in which the items are presented affects people’s responses.

A questionnaire item that allows participants to answer in whatever way they choose.

A questionnaire item that asks a question and provides a set of response options for participants to choose from.

An ordered set of responses that participants must choose from.

A guideline for questionnaire items that suggests they should be brief, relevant, specific, and objective.

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

Share This Book

• Solutions Industry Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use case NPS+ Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Employee Experience Conjoint
• Resources Blog eBooks Survey Templates Case Studies Training Help center

Thesis Survey

• Desktop Created with Sketch.
• Mobile Created with Sketch.

Related templates and questionnaires

• Sample Questions
• Sample Reports
• Survey Logic
• Integrations
• Professional Services
• Survey Software
• Customer Experience
• Communities
• Polls Explore the QuestionPro Poll Software - The World's leading Online Poll Maker & Creator. Create online polls, distribute them using email and multiple other options and start analyzing poll results.
• Research Edition
• Survey Templates
• Case Studies
• Coronavirus Resources
• Qualtrics Explore the list of features that QuestionPro has compared to Qualtrics and learn how you can get more, for less.
• SurveyMonkey
• VisionCritical
• Market Research Survey Software Real-time, automated and advanced market research survey software & tool to create surveys, collect data and analyze results for actionable market insights.
• Employee Survey Software Employee survey software & tool to create, send and analyze employee surveys. Get real-time analysis for employee satisfaction, engagement, work culture and map your employee experience from onboarding to exit!
• Customer Survey Software Robust, automated and easy to use customer survey software & tool to create surveys, real-time data collection and robust analytics for valuable customer insights.
• Community Survey Software Use the community survey software & tool to create and manage a robust online community for market research. Collect community feedback and insights from real-time analytics!
• Web Survey Software Powerful web survey software & tool to conduct comprehensive survey research using automated and real-time survey data collection and advanced analytics to get actionable insights.
• Mobile Survey Software Leverage the mobile survey software & tool to collect online and offline data and analyze them on the go. Create and launch smart mobile surveys!
• Business Survey Software Powerful business survey software & tool to create, send and analyze business surveys. Get actionable insights with real-time and automated survey data collection and powerful analytics!
• Enterprise Survey Software Real time, automated and robust enterprise survey software & tool to create surveys. collect data and analyze responses to get quick actionable insights.
• Email Survey Software Robust email survey software & tool to create email surveys, collect automated and real-time data and analyze results to gain valuable feedback and actionable insights!
• SMS Survey Software Use the power of SMS to send surveys to your respondents at the click of a button. SMS survey software and tool offers robust features to create, manage and deploy survey with utmost ease.
• Offline Surveys
• Customer Satisfaction Surveys
• Net Promoter Score (NPS) Learn everything about Net Promoter Score (NPS) and the Net Promoter Question. Get a clear view on the universal Net Promoter Score Formula, how to undertake Net Promoter Score Calculation followed by a simple Net Promoter Score Example.
• Conjoint Analysis
• GDPR & EU Compliance
• Likert Scale Complete Likert Scale Questions, Examples and Surveys for 5, 7 and 9 point scales. Learn everything about Likert Scale with corresponding example for each question and survey demonstrations.
• Executive Team
• Advisory Board
• Testimonials
• In the news

QuestionPro in your language

• Encuestas Online
• Pesquisa Online
• Umfrage Software
• Сервис опросов
• برامج للمسح
• Logiciel d'enquête

Awards & certificates

The experience journal.

Find innovative ideas about Experience Management from the experts

• Privacy Statement
• Terms of Use
• Cookie Settings

Creating a survey with QuestionPro is optimized for use on larger screens -

Though you're welcome to continue on your mobile screen, we'd suggest a desktop or notebook experience for optimal results.