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Qualitative study design: Surveys & questionnaires

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Surveys & questionnaires

Qualitative surveys use open-ended questions to produce long-form written/typed answers. Questions will aim to reveal opinions, experiences, narratives or accounts. Often a useful precursor to interviews or focus groups as they help identify initial themes or issues to then explore further in the research. Surveys can be used iteratively, being changed and modified over the course of the research to elicit new information. 

Structured Interviews may follow a similar form of open questioning.  

Qualitative surveys frequently include quantitative questions to establish elements such as age, nationality etc. 

Qualitative surveys aim to elicit a detailed response to an open-ended topic question in the participant’s own words.  Like quantitative surveys, there are three main methods for using qualitative surveys including face to face surveys, phone surveys, and online surveys. Each method of surveying has strengths and limitations.

Face to face surveys  

• Researcher asks participants one or more open-ended questions about a topic, typically while in view of the participant’s facial expressions and other behaviours while answering. Being able to view the respondent’s reactions enables the researcher to ask follow-up questions to elicit a more detailed response, and to follow up on any facial or behavioural cues that seem at odds with what the participants is explicitly saying.
• Face to face qualitative survey responses are likely to be audio recorded and transcribed into text to ensure all detail is captured; however, some surveys may include both quantitative and qualitative questions using a structured or semi-structured format of questioning, and in this case the researcher may simply write down key points from the participant’s response.

Telephone surveys

• Similar to the face to face method, but without researcher being able to see participant’s facial or behavioural responses to questions asked. This means the researcher may miss key cues that would help them ask further questions to clarify or extend participant responses to their questions, and instead relies on vocal cues.

Online surveys

• Open-ended questions are presented to participants in written format via email or within an online survey tool, often alongside quantitative survey questions on the same topic.
• Researchers may provide some contextualising information or key definitions to help ‘frame’ how participants view the qualitative survey questions, since they can’t directly ask the researcher about it in real time. 
• Participants are requested to responses to questions in text ‘in some detail’ to explain their perspective or experience to researchers; this can result in diversity of responses (brief to detailed).
• Researchers can not always probe or clarify participant responses to online qualitative survey questions which can result in data from these responses being cryptic or vague to the researcher.
• Online surveys can collect a greater number of responses in a set period of time compared to face to face and phone survey approaches, so while data may be less detailed, there is more of it overall to compensate.

Qualitative surveys can help a study early on, in finding out the issues/needs/experiences to be explored further in an interview or focus group. 

Surveys can be amended and re-run based on responses providing an evolving and responsive method of research. 

Online surveys will receive typed responses reducing translation by the researcher 

Online surveys can be delivered broadly across a wide population with asynchronous delivery/response. 

Limitations

Hand-written notes will need to be transcribed (time-consuming) for digital study and kept physically for reference. 

Distance (or online) communication can be open to misinterpretations that cannot be corrected at the time. 

Questions can be leading/misleading, eliciting answers that are not core to the research subject. Researchers must aim to write a neutral question which does not give away the researchers expectations. 

Even with transcribed/digital responses analysis can be long and detailed, though not as much as in an interview. 

Surveys may be left incomplete if performed online or taken by research assistants not well trained in giving the survey/structured interview. 

Narrow sampling may skew the results of the survey. 

Example questions

Here are some example survey questions which are open ended and require a long form written response:

• Tell us why you became a doctor? 
• What do you expect from this health service? 
• How do you explain the low levels of financial investment in mental health services? (WHO, 2007) 

Example studies

• Davey, L. , Clarke, V. and Jenkinson, E. (2019), Living with alopecia areata: an online qualitative survey study. British Journal of Dermatology, 180 1377-1389. Retrieved from https://onlinelibrary-wiley-com.ezproxy-f.deakin.edu.au/doi/10.1111%2Fbjd.17463    
• Richardson, J. (2004). What Patients Expect From Complementary Therapy: A Qualitative Study. American Journal of Public Health, 94(6), 1049–1053. Retrieved from http://ezproxy.deakin.edu.au/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=s3h&AN=13270563&site=eds-live&scope=site  
• Saraceno, B., van Ommeren, M., Batniji, R., Cohen, A., Gureje, O., Mahoney, J., ... & Underhill, C. (2007). Barriers to improvement of mental health services in low-income and middle-income countries. The Lancet, 370(9593), 1164-1174. Retrieved from https://www-sciencedirect-com.ezproxy-f.deakin.edu.au/science/article/pii/S014067360761263X?via%3Dihub  

Below has more detail of the Lancet article including actual survey questions at: 

• World Health Organization. (2007.) Expert opinion on barriers and facilitating factors for the implementation of existing mental health knowledge in mental health services. Geneva: World Health Organization. https://apps.who.int/iris/handle/10665/44808
• Green, J. 1961-author., & Thorogood, N. (2018). Qualitative methods for health research. SAGE. Retrieved from http://ezproxy.deakin.edu.au/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=cat00097a&AN=deakin.b4151167&authtype=sso&custid=deakin&site=eds-live&scope=site   
• JANSEN, H. The Logic of Qualitative Survey Research and its Position in the Field of Social Research Methods. Forum Qualitative Sozialforschung, 11(2), Retrieved from http://www.qualitative-research.net/index.php/fqs/article/view/1450/2946  
• Neilsen Norman Group, (2019). 28 Tips for Creating Great Qualitative Surveys. Retrieved from https://www.nngroup.com/articles/qualitative-surveys/   
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28 tips for creating great qualitative surveys.

September 25, 2016 2016-09-25

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Qualitative surveys ask open-ended questions to find out more, sometimes in preparation for doing quantitative surveys. Test surveys to eliminate problems.

Sooner or later, most UX professionals will need to conduct a survey. Survey science from the quantitative side can be intimidating because it’s a specialized realm full of statistics, random selection, and scary stories of people going wrong with confidence. Don’t be afraid of doing qualitative surveys, though. Sure, it’s important to learn from survey experts, but you don’t have to be a survey specialist to get actionable data. You do have to find and fix the bugs in your questions first, however.

In This Article:

Quantitative vs. qualitative surveys, tips for qualitative surveys.

Quantitative surveys count results : how many people do this vs. do that (or rather, how many say that they do this or that). Use quant surveys when you need to ask questions that can be answered by checkbox or radio button, and when you want to be sure your data is broadly applicable to a large number of people. Quantitative surveys follow standard methods for randomly selecting a large number of participants (from a target group) and use statistical analysis to ensure that the results are statistically significant and representative for the whole population.

Qualitative surveys ask open-ended questions . Use them when you need to generate useful information via a conversation rather than a vote, such as when you’re not sure what the right set of answers might include. Qualitative surveys ask for comments, feedback, suggestions, and other kinds of responses that aren’t as easily classified and tallied as numbers can be. You can survey fewer people than in a quantitative survey and get rich data.

It’s possible to mix the two kinds of surveys, and it’s especially useful to do small, primarily qualitative surveys first to help you generate good answers to count later in a bigger survey. This one-two-punch strategy is much preferable to going straight to a closed-ended question with response categories you and your colleagues thought up in your conference room. (Yes, you could add an “other” option, but don’t count on valid statistics for options left to a catch-all bucket.)

Unordered lists can be more time-consuming to look through than lists that have an obvious ordering principle, but unordered lists seem to yield better answers, especially if you can sort the list differently for different respondents.

• Draft questions and get feedback from colleagues.
• Draft survey and get colleagues to attempt to answer the questions. Ask for comments after each question to help you revise questions toward more clarity and usefulness.
• Revise survey and test iteratively on paper. We typically do 4 rounds of testing, with 1 respondent per round. At this stage, don’t rely on colleagues, but recruit participants from the target audience. Revise between each round. Run these tests as think-aloud studies ; do not send out the survey and rely on written comments — they will never be the same as a realtime stream of commentary.
• Randomize some sections and questions of the survey to help ensure that (1) people quitting partway through don’t affect the overall balance of data being collected, and (2) the question or section ordering doesn’t bias people’s responses.
• Test the survey-system format with a small set of testers from the target audience, again collecting comments on each page.
• Examine the output from the test survey to ensure the data gathered is in an analyzable, useful format.
• Revise the survey one more time.
• Don’t make your own tool for surveys if you can avoid it . Many solid survey platforms exist, and they can save you lots of time and money.
• Decide up front what the survey learning goals are . What do you want to report about? What kind of graphs and tables will you want to deliver?
• Write neutral questions that don’t imply particular answers or give away your expectations .
• Open vs. closed answers : Asking open-ended questions is the best approach, but it’s easy to get into the weeds in data analysis when every answer is a paragraph or two of prose. Plus, users quickly tire of answering many open-ended questions, which usually require a lot of typing and explanation. That being said, it’s best to ask open-ended questions during survey testing . The variability of the answers to these questions during the testing phase can help you decide whether the question should be open-ended in the final survey or could be replaced with a closed-ended question that would be easier to answer and analyze.
• Carefully consider how you will analyze and act on the data . The type of questions you ask will have everything to do with the kind of analysis you can make: multiple answers, single answers, open or closed sets, optional and required questions, ratings, rankings, and free-form answer fields are some of the choices open to you when deciding what kinds of answers to accept. (If you won’t act on the data, don’t ask that question. See guideline #12.)
• Multiple vs. single answers : Often multiple-answer questions are better than single-answer ones because people usually want to be accurate, and often several answers apply to them. Survey testing on paper can help you find multiple-answer questions, because people will mark several answers even when you ask them to mark only one (and they will complain about it). If you are counting answers, consider not only how many responses each answer got, but also how many choices people made.
• Front-load the most important questions, because people will quit partway through . Ensure that partial responses will be recorded anyway.
• Provide responses such as, “Not applicable” and “Don’t use” to prevent people skipping questions or giving fake answers. People get angry when asked questions they can’t answer honestly, and it skews your data if they try to do it anyway.
• People have trouble understanding required and optional signals on survey question/forms . It’s common practice to use a red asterisk “ * ” to mark required fields, but that didn’t work well enough, even in a survey of UX professionals — many of whom likely design such forms. People complained that required fields were not marked. Pages that stated at the top that all were required or optional also didn’t help, because many people ignore instruction text. Use “(Optional)” and/or “(Required)” after each question, to be sure people understand.
• When marking is not clear enough, many people feel obligated to answer optional questions . Practically speaking that means you don’t have to require every question, but you should be careful not to include so many questions that people quit the survey in the middle.
• Keep it short . Every extra question reduces your response rate, decreases validity, and makes all your results suspect. Better to administer 2 short surveys to 2 different subsamples of your audience than to lump everything you want to know into a long survey that won’t be completed by the average customer. 20 questions are too many unless you have a highly motivated set of participants. People are much more likely to participate in 1-question surveys. Be sensitive to what your pilot testers tell you, and realistically estimate the time to complete the survey. The more open-ended questions and complex ranking you ask people to do, the more you’ll lose respondents.
• People often overlook examples and instructions that are on the right , after questions. Move instructions and examples to the left margin instead (or the opposite side, for languages that read right to left), to put them in the scannability zone and place them closer to the person’s focus of attention, which is on the answer area.
• Use one-line directions if you can. Less is more. Just as in our original writing for the web studies , people read more text when there is a lot less of it. People complain about not getting enough information, but when it’s there they don’t read it because it’s too long.
• People tend not to read paragraphs or introductions . If you must use a paragraph, bold important ideas to help ensure that most people, who scan instead of reading , glean that information.
• Think carefully about using subjective terms , such as “essential,” “useful,” or “frequent.” Terms that cause people to make a judgment call may get at how they feel, but such questions can be confusing to evaluate logically. Ratings scales are more flexible. If you do need to know how participants perceive a certain aspect, indicate that’s what you want them to base their answer on (for example, instead of asking “Is X essential for Y?” say “Do you feel that X is essential for Y?”).
• Define terms as needed in order to start from a shared meaning. People might quibble about the definition, but it’s better than getting misleading answers because of a misinterpretation.
• Don’t ask about things that your analytics can tell you . Ask why and how questions.
• Include a survey professional in your test group . Your survey method may be criticized after the fact, so get expert advice before you conduct your survey.
• Items at the top and bottom of lists may attract more attention than items in the middle of long lists.
• Because people scan instead of read, the first words of items in lists can cause them to overlook the right choice, especially in alphabetical lists.
• Test where best to place page breaks. Sometimes it’s important for people to be able to see all the topic’s questions before they answer one. Otherwise they volunteer answers for the questions they have not yet seen and write, “see previous answer” later, which adds extra interpretation steps in data analysis. To find questions with these kinds of problems, you can test the survey with each question on its own page first, and then collocate the questions that need to be shown together on one page in the next test version. In some cases, simply forcing one question to come before another one can fix these problems.
• If possible, don’t annoy people by asking questions that don’t apply to them . When respondents choose a particular answer, show them one or two more questions about that topic that would be applicable in that case. Choose a survey platform that allows conditional questions, so you can avoid presenting nonapplicable questions and keep your list of questions as short as possible for each respondent. If most of your questions are conditional, you might be able to put a key conditional question early in the list, then branch to different versions of the survey for the rest of the questions.
• Take your data with a grain of salt . Unlike for quantitative surveys, qualitative survey metrics are rarely representative for the whole target audience; instead, they represent the opinions of the respondents. You can still present descriptive statistics (such as how many people selected a specific response to a multiple-choice question) to summarize the results of the survey, but, unless you use sound statistics tools, you cannot say whether these results are the result of noise or sample selection, as opposed to truly reflecting the attitudes of your whole user population.
• Count whatever you can count . Researchers often refer to coding and normalizing data during analysis. Coding data is the process of making text answers into something you can count, so you can extract the bigger trends and report them in a way that makes sense to your report audience. You can capture rich textual data for understanding and quoting, and code some types of responses as 0, 1, or 2 (no, partially, yes; or none, some, all) for example, or you may be able to define many different phrases as meaning the same thing (for example when people use synonyms or express the same ideas). This coding can be done after the data is collected, in a spreadsheet.
• Show, don’t tell . Use lots of graphs, charts, and tables, with an executive summary of key takeaways.
• Consider graphs before you decide on a spreadsheet layout . Unfortunately some spreadsheets won’t make reasonable graphs until you switch columns to rows or rows to columns. It’s easiest to plan for this necessity before you analyze your data. It’s also possible to take the chart data, put it on its own spreadsheet page, and then reorder it to make the charts. Just be careful not to make data transfer errors.
• Beware of disappearing chart data . Some spreadsheets hide data in charts silently when font-size changes or chart-size changes are made.
• Don’t embed data if you can screenshot it . Screenshots (PNG format is recommended) are lovely and robust over time, unlike embedded data, which tends to cause document corruption, become unlinked, or could be changed by mistake.

Qualitative surveys are tools for gathering rich feedback. They can also help you discover which questions you need to ask and the best way to ask them, for a later quantitative survey. Improve surveys through iterative testing with open-ended feedback. Test surveys on paper first to save time-consuming rework in the testing platform. Then test online to see the effects of page order and question randomization and to gauge how useful the automated results data may be.

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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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10+ Qualitative Survey Questions to Collect Deep Insights

Just like great ingredients are the basis for preparing an amazing meal, a great survey needs to have amazing questions. And unless you know the recipe by heart, choosing effective survey questions can be difficult. One of the most common choices you can make are qualitative survey questions.

They let you uncover deep insights with qualitative research, but they do come with some challenges. In this article, we’ll show you how to write great qualitative questions, what makes them good (and bad) choices for your qualitative surveys, as well as some examples to get you inspired.

Qualitative vs. quantitative questions

Before we go any further, we need to make a distinction between qualitative and quantitative survey questions .

Qualitative questions help you get qualitative data. These are the questions that get behind the why, what, and how of a particular subject through qualitative research of your focus groups. An example of a qualitative question would be: Please describe your recent experience with our customer support.

Use qualitative research questions when you need customers to explain their experience in their own words and provide you with deeper insights. 

Quantitative questions help you collect quantitative, numerical data. They help you put a numerical value on your customers’ feedback. An example of a quantitative question would be: “On a scale from 1 to 10, please rate your satisfaction with your recent experience with our customer support?”

‍ Use quantitative research questions when you need data that is easy to analyze and quantify so that you can make an important decision based on data.

Both question types have their pros and cons, and depending on your needs, you’ll want to use one or the other or a combination of both research methods on your target audience.

How to write good qualitative survey questions

Qualitative survey questions can unearth impressive data. However, you need to be very careful about how you write them to get the best feedback from your focus groups. Here are some quick tips to get started.

Make the qualitative research questions specific

The first rule is very simple. A qualitative question leaves your audience with a space to write anything they want. And the truth is, they will literally write anything if you don’t point them in the right direction.

If your survey questions are too broad, they will result in broad answers and feedback that is not particularly useful. For example, asking “How do you like our dashboard?” is going to give you a wide range of answers.

Instead, ask something along the lines of “What do you think of the different visualization styles in our reporting dashboard?”

The more specific the survey questions, the better the feedback. 

Have a clear purpose

Why are you asking a certain question? In the case of quantitative surveys, you don’t always need a specific reason, e.g. checking up on your NPS score .

However, qualitative questions demand lengthier answers and you need to motivate your target audience to provide that answer. The best way to do so? Just let them know why you’re asking.

For example, you could say that you’re asking about the checkout process in order to make it quicker to purchase and easier to choose a preferred payment method. The stronger the benefit for the customer, the more reasons for stating the purpose of the survey.

Focus on quality, not numbers

You won’t get the same number of answers with qualitative questions compared to quantitative ones such as CSAT surveys . Put simply, writing out an answer takes more time than selecting a number on a scale.

You may be tempted to simplify your survey questions to get more answers from your survey participants. However, try and resist the temptation.

Your aim is to get amazing feedback so don’t shy away from asking the survey questions that really interest you. Five good answers are much better than 50 superficial ones you can’t use.

Add subquestions when necessary

Sometimes, you can’t get all the info you need from one answer. If you want to ensure you get all the feedback you need, asking a subquestion makes sense.

For example, you could ask customers about their thoughts on a new feature you launched. A subquestion could be one where you ask the customers what would make them use that feature more.

You can actually ask this question in a matter of seconds by using this survey template:

Your customers are willing to provide feedback to help you out, but you sometimes need to nudge them in the right direction.

Pros and cons of using qualitative questions for surveys

Qualitative survey questions can yield amazing results. However, they have their good and bad sides, and you need to be aware of both before creating your next survey.

Advantages of using qualitative questions in surveys

Let’s start with the good stuff.

They help you get in-depth data

A quantitative question tells you how likely someone is to recommend you on a scale. While a number is a good piece of info, a few sentences describing why and how they would recommend you will provide the context. If you want in-depth data where customers describe how they feel about you in more detail, you need qualitative research questions.

They are more flexible by nature

The typical quantitative question has a standard form. Survey types such as CSAT, NPS, and CES have question formats that don’t vary much. On the other hand, the sky is the limit with qualitative research questions. You can phrase them in any way you want, using specific expressions to narrow down the type of feedback you want to get.

They encourage discussion

There is little that can happen once an NPS survey is complete. You get the results, analyze them (in minutes, thanks to Survicate’s dashboard ), and the conversation is over. Qualitative research questions encourage your customers to speak their minds and share how they feel.

Disadvantages of using qualitative survey questions

There are some downsides to keep in mind with this question type.

The sample size

Qualitative data is amazing when it comes to the insights that you get. But on the flip side, it requires detailed analysis, and you have to manually go through all the survey responses to find the gold nuggets in your feedback. As a result, the sample is usually much smaller than in quantitative surveys, and you have to use focus groups with limited respondent numbers.

Sample bias

With the smaller size sample usually comes the sample bias . This means that you’ll tend to pick customers who are similar in some way, including demographics, use cases, location, and your data might be skewed. 

Lack of privacy

Lots of data is always a great thing for businesses, but there may be some concerns from the customers’ end. 

If they give you detailed answers, you can accurately pinpoint the identity of the customer who supplied the answer. You can solve a part of the problem by making the survey anonymous , but bear in mind that some customers will be concerned about privacy issues regardless.

Difficulty with statistical analysis

Imagine 500 respondents filled in your NPS survey. You could get your NPS score within seconds using survey software like Survicate. On the other hand, getting qualitative research results from a focus group with 500 people could take weeks. Be prepared to set aside some time to go through the responses to your qualitative surveys manually.

Qualitative question examples

Here are some amazing qualitative question examples to get you inspired. You can adapt these to a specific use case depending on your industry and niche.

Exploratory questions

The most common of the qualitative research questions, the exploratory question aims to just… explore. You ask your survey participants about a particular topic so you can learn more about their thoughts, experiences, and attitudes.

• Describe the last interaction you had with our product.
• Does our product meet your overall expectations?
• What is the most valuable feature in our product?
• Why did you choose to use our product compared to the competitors?
• What is the one aspect of our product that you never use?
• What is your biggest objection to our checkout process and why?

Predictive questions

Predictive survey questions put survey participants in a certain situation. Based on past events, you ask them to predict what would happen in a hypothetical situation. If you phrase the questions correctly, they can provide a wealth of feedback about the respondents’ pain points and your product.

• If we added free returns on all orders above $50, would you shop more with us?
• If you could add one more feature to our product, what would that feature be and why?
• If we had a Zapier integration for our app, how often would you use it?
• If you were in charge of our customer support for a day, what would you change and why?
• Would you be more likely to buy our product if it was endorsed by a large company such as Microsoft?

Get ready for deep insights with qualitative questions in your surveys

Not everyone is born a great writer or a qualitative research expert. But nowadays, you don’t have to be either of those things to write amazing qualitative questions and have great qualitative surveys.

Survey software has come a long way and nowadays, it does more than just provide a platform for creating and distributing online surveys. Survicate comes with 125+ survey templates out of the box, packed with quantitative and qualitative questions, ready to use.

Kickstart your qualitative research today by choosing the right tool for the job. Try Survicate and see why online surveys are the future of conducting qualitative research.

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Qualitative Research Questions: What it is and how to write it

Qualitative research questions are like a compass that points researchers in the right direction to find rich stories, untangle complicated social relationships, and get a clear picture of how people act in subtle ways. Unlike their quantitative counterparts, these questions go beyond numbers and figures to explore the subjective, contextual, and complex parts of the human experience.

It’s well-established that all forms of research come with their own theories and implementation methods. Qualitative research is much the same. Qualitative research is conducted to understand the thought process of both the respondents as well as researchers. It usually is conducted in a natural setup where respondents will be their true selves and would respond transparently. 

Results achieved from this research will not be generalized to the entire population but asked research questions , and their vocabulary gives away the researcher’s motive making it easier for respondents to participate in qualitative market research .

LEARN ABOUT: Research Process Steps

Qualitative research survey questions are created to understand a particular topic better or to inspect a new subject to understand the nerve of respondent experiences.

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What are qualitative research questions?

How to write qualitative research questions, types of qualitative research questions, how to choose qualitative research questions, what should be the process of forming qualitative research questions and questionnaires.

Qualitative research questions are the inquiries that lead to qualitative research studies and investigations. They are meant to help people explore and understand phenomena, experiences, meanings, and views from the participant’s point of view. 

Different from quantitative research questions, which often try to measure and quantify variables, qualitative research questions try to understand the richness and complexity of human experiences and social events.

Most qualitative research questions are open-ended and allow for in-depth study. They want more than simple yes/no answers but instead want people to talk about their thoughts, feelings, views, and experiences. These questions try to find deeper meanings, patterns, and connections in a given situation.

Here are some examples of qualitative study questions in different fields:

• In psychology: How do individuals experience and cope with traumatic events?
• In sociology: What factors influence a student’s decision to pursue higher education?
• In anthropology: How do cultural norms and values shape gender roles in a specific community?
• In education: What are the challenges faced by teachers in implementing project-based learning in the classroom?
• In healthcare: What are the experiences and perspectives of patients undergoing long-term treatment for a chronic illness?

Qualitative research questions should be straightforward, specific, and tailored to the research’s goals. They guide the process of gathering data through interviews, observations, or document analysis and give a method for analyzing and interpreting data.

Writing the right qualitative research questions requires careful thought about the research goals, the event being studied, and the wanted level of understanding. Here are some tips to help you write good qualitative research questions:

Begin with a broad research question

Start by posing an all-encompassing question that probes the subject or phenomenon of interest. Exploring and learning from the answer to this open-ended question should be possible.

Specify the research objectives

Clearly state the objectives and purposes of your research. What do you want your qualitative study to accomplish? What facets or dimensions of the subject do you wish to investigate?

Focus on the phenomenon

Decide on whatever specific subject or phenomenon you want to research. Any pertinent topic, including social behavior, cultural customs, personal experiences, and more, may be used.

Use open-ended and exploratory language

In qualitative research, open-ended questions should be used to enable participants to offer thorough and in-depth responses. Avoid yes/no questions and queries with a one-word answer. Use words like “how,” “what,” “why,” or “describe” instead to compel people to express their thoughts and experiences.

LEARN ABOUT: Qualitative Interview

Consider the context and participants

Consider your research’s background as well as the qualities of your subjects. Make sure your qualitative methods are specific to the people you will be studying so that they are pertinent and meaningful to them.

Incorporate theory and literature

Your research questions should be based on pertinent theories and available literature. This gives your investigation a theoretical foundation and places your study within the body of knowledge.

Balance breadth and depth

When formulating your research topics, try to strike a balance between depth and breadth. To fully understand the subject, you should investigate it broadly to get a variety of viewpoints and intensively delve into certain areas.

Avoid leading or biased questions

Ensure your questions are neutral and unbiased. Avoid leading participants towards a particular response. Instead, create questions that allow participants to express their thoughts and experiences freely.

Pilot test your questions

Pilot-test your research questions with a small group of people before finalizing them. This will make it easier to spot any possible problems, ambiguities, or places where clarity may be increased.

Revise and refine

Revise and clarify your research questions based on the comments and understandings received from the pilot testing. Aim for consistency, coherence, and congruence with your research goals.

Remember, qualitative market research questions should be flexible and adaptable throughout the research process. They serve as a guide but may evolve as you delve deeper into the data and discover new insights.

LEARN ABOUT: Steps in Qualitative Research

There are several types of qualitative research questions focus that can be used to guide qualitative studies. Here are some common types:

1. Descriptive questions

These questions aim to describe and understand a phenomenon or topic in detail. They focus on providing a comprehensive account of the subject matter. For example:

• What are the experiences of individuals living with chronic pain?
• How do employees perceive the organizational culture in a specific company?

2. Exploratory questions

These questions are used to explore new or under-researched areas. They seek to gain a deeper understanding of a topic or phenomenon. For example:

• What are the factors influencing consumers’ decision-making process when purchasing organic food?
• How do teachers perceive the implementation of project-based learning in the classroom?

3. Experiential questions

These questions focus on understanding individuals’ experiences, perspectives, and subjective meanings related to a particular phenomenon. They aim to capture personal experiences and emotions. For example:

• What are the challenges first-generation college students face during their transition to higher education?
• How do individuals with social anxiety disorder experience social interactions?

4. Comparative questions

These questions involve comparing and contrasting different groups, contexts, or perspectives to identify similarities, differences, or patterns. They explore variations in experiences or phenomena. For example:

• How do parenting practices differ between cultures A and B in terms of child discipline?
• What are the similarities and differences in the coping strategies used by individuals with individuals and depression questionnaire with anxiety disorders?

5. Process-oriented questions

These questions focus on understanding a phenomenon’s processes, mechanisms, or dynamics. They aim to uncover how and why certain outcomes or behaviors occur. For example:

• What are the processes by which teams in a workplace reach a consensus on decision-making?
• How does the negotiation process unfold during conflict resolution in interpersonal relationships?

6. Theoretical questions

These questions seek to generate or refine theory. They explore concepts, relationships, or theoretical frameworks to contribute to the existing body of knowledge. For example:

• How does the concept of “self-efficacy” manifest in the context of entrepreneurship?
• What underlying mechanisms explain the relationship between social support and mental health outcomes?

These are just a few examples of the types of qualitative research questions that can be used. The specific type of question you choose will depend on your research objectives, the phenomenon under investigation, and the depth of understanding you aim to achieve.

Explore Insightfully Contextual Inquiry in Qualitative Research

Choosing a good qualitative research question involves a thoughtful and systematic approach to ensure they align with the objectives of your study and allows for an in-depth exploration of the topic. Here are some steps to help you choose effective qualitative research questions:

Identify your research objectives

Clearly define the purpose of your study. What do you want to explore or understand? What specific insights or knowledge are you seeking to gain through your market research?

Review existing literature

Conduct a thorough review of relevant literature to identify existing research gaps or areas requiring further exploration. This will help you understand the current state of knowledge and inform the development of your research questions.

Brainstorm potential qualitative research question

Generate a list of potential research questions that address your research objectives. Consider different angles, perspectives, and dimensions of your topic. Creating open-ended questions that allow for in-depth exploration rather than simple yes/no answers is important.

Prioritize and refine the questions

Evaluate the generated questions based on their relevance to your research objectives, feasibility, and potential to yield meaningful insights. Prioritize the questions that are most likely to provide rich and valuable data. Refine and rephrase the questions as needed to ensure clarity and focus.

Consider the research design and methodology

Take into account the specific qualitative research design and methodology you plan to use. Different research approaches, such as ethnography, interviews, focus groups, or case studies, may require different types of research questions. Ensure that your questions align with your chosen methodology and will help you gather the desired data.

Pilot test the questions

Before finalizing your research questions, consider conducting a pilot test with a small group of participants. This will allow you to assess your questions’ clarity, appropriateness, and effectiveness. Make necessary revisions based on the feedback received.

Seek feedback

Share your research questions with colleagues, mentors, or experts in your field for feedback and suggestions. They can provide valuable insights and help you refine your questions further.

Finalize your research questions

Based on the steps above, select a set of research questions that are well-aligned with your research objectives, provide scope for exploration, and are feasible within the resources and time available for your study.

1. Mention the purpose of conducting qualitative research. It can be in the form of either of these sentences:

• This study will be on the topic of ….
• The reason for conducting this research is ….

2. Create qualitative statements with a defined objective that can be easily communicated to the target audience .

Keep these pointers in mind while designing this statement:

• Try and form single-sentence statements. Single statements can be much more effective than elaborate ones as they help in communicating important messages in an impactful manner in a short and succinct sentence.
• Clarify the purpose of conducting qualitative research in clear words so that respondents understand their contribution to this research.
• Mention the main topic of research that would prompt respondents to have a clearer idea about what they’re getting into.
• It’s the words that make all the difference. Use qualitative words that demonstrate the quality or feeling behind your purpose, such as understanding, describing, explore.
• Specify details that you would want to communicate to your respondents.
• Mention the name of the research website.

3. Other than the primary qualitative questions, you must create sub-questions so that the purpose is executed in a better manner.

• The main question might be – “What is the state of illiteracy in your state?”
• You can create sub-questions such as: “How does illiteracy hamper progress in your state?” or “How would you best describe your feelings about illiteracy?”

4. Highlight these questions using ‘qualitative’ words:

• Start the questions with “What” or “How” to make sure the respondents provide details about their feelings.
• Communicate what you’re trying to “understand,” “explore,” or “identify” using this Qualitative research online survey questionnaire.
• Questions such as “What happened” can be asked to develop a description of the topic.
• Questions about “how did respondents interpret the what happened question” can be asked to examine the outcome.
• Understand the entire qualitative research process by asking questions about “What happened to you with time?”

5. Develop a skeleton to design the primary questions and also the sub-questions. For example:

• Primary Qualitative research survey question: “How do you think _______ (the main topic of research) means?” or “Describe _____(the main topic of research) as you’ve experienced.”
• Sub-question for qualitative research: “What _________ (characteristic) does __________ (respondents) interest in as a _________ (main topic of research)?”

LEARN ABOUT: Structured Questionnaire

Qualitative research questions are key to giving research studies depth and breadth. These questions go into the details and complexities of human experiences, perceptions, and behaviors. This helps researchers get a full picture of a certain occurrence. 

Qualitative research questions are meant to explore, describe, and make sense of subjective truths. Most of the time, they are open-ended, so people can say what they think and feel in their own words. 

QuestionPro is an online poll and research platform with several tools and features that can make it easier to make and use qualitative research questions. Its easy-to-use design and variety of question types help researchers collect qualitative data quickly and easily, improving the whole research process.

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Your ultimate guide to qualitative research (with methods and examples).

16 min read You may be already using qualitative research and want to check your understanding, or you may be starting from the beginning. Learn about qualitative research methods and how you can best use them for maximum effect.

What is qualitative research?

Qualitative research is a research method that collects non-numerical data. Typically, it goes beyond the information that quantitative research provides (which we will cover below) because it is used to gain an understanding of underlying reasons, opinions, and motivations.

Qualitative research methods focus on the thoughts, feelings, reasons, motivations, and values of a participant, to understand why people act in the way they do .

In this way, qualitative research can be described as naturalistic research, looking at naturally-occurring social events within natural settings. So, qualitative researchers would describe their part in social research as the ‘vehicle’ for collecting the qualitative research data.

Qualitative researchers discovered this by looking at primary and secondary sources where data is represented in non-numerical form. This can include collecting qualitative research data types like quotes, symbols, images, and written testimonials.

These data types tell qualitative researchers subjective information. While these aren’t facts in themselves, conclusions can be interpreted out of qualitative that can help to provide valuable context.

Because of this, qualitative research is typically viewed as explanatory in nature and is often used in social research, as this gives a window into the behavior and actions of people.

It can be a good research approach for health services research or clinical research projects.

Free eBook: The qualitative research design handbook

Quantitative vs qualitative research

In order to compare qualitative and quantitative research methods, let’s explore what quantitative research is first, before exploring how it differs from qualitative research.

Quantitative research

Quantitative research is the research method of collecting quantitative research data – data that can be converted into numbers or numerical data, which can be easily quantified, compared, and analyzed .

Quantitative research methods deal with primary and secondary sources where data is represented in numerical form. This can include closed-question poll results, statistics, and census information or demographic data.

Quantitative research data tends to be used when researchers are interested in understanding a particular moment in time and examining data sets over time to find trends and patterns.

The difference between quantitative and qualitative research methodology

While qualitative research is defined as data that supplies non-numerical information, quantitative research focuses on numerical data.

In general, if you’re interested in measuring something or testing a hypothesis, use quantitative research methods. If you want to explore ideas, thoughts, and meanings, use qualitative research methods.

While qualitative research helps you to properly define, promote and sell your products, don’t rely on qualitative research methods alone because qualitative findings can’t always be reliably repeated. Qualitative research is directional, not empirical.

The best statistical analysis research uses a combination of empirical data and human experience ( quantitative research and qualitative research ) to tell the story and gain better and deeper insights, quickly.

Where both qualitative and quantitative methods are not used, qualitative researchers will find that using one without the other leaves you with missing answers.

For example, if a retail company wants to understand whether a new product line of shoes will perform well in the target market:

• Qualitative research methods could be used with a sample of target customers, which would provide subjective reasons why they’d be likely to purchase or not purchase the shoes, while
• Quantitative research methods into the historical customer sales information on shoe-related products would provide insights into the sales performance, and likely future performance of the new product range.

Approaches to qualitative research

There are five approaches to qualitative research methods:

• Grounded theory: Grounded theory relates to where qualitative researchers come to a stronger hypothesis through induction, all throughout the process of collecting qualitative research data and forming connections. After an initial question to get started, qualitative researchers delve into information that is grouped into ideas or codes, which grow and develop into larger categories, as the qualitative research goes on. At the end of the qualitative research, the researcher may have a completely different hypothesis, based on evidence and inquiry, as well as the initial question.
• Ethnographic research : Ethnographic research is where researchers embed themselves into the environment of the participant or group in order to understand the culture and context of activities and behavior. This is dependent on the involvement of the researcher, and can be subject to researcher interpretation bias and participant observer bias . However, it remains a great way to allow researchers to experience a different ‘world’.
• Action research: With the action research process, both researchers and participants work together to make a change. This can be through taking action, researching and reflecting on the outcomes. Through collaboration, the collective comes to a result, though the way both groups interact and how they affect each other gives insights into their critical thinking skills.
• Phenomenological research: Researchers seek to understand the meaning of an event or behavior phenomenon by describing and interpreting participant’s life experiences. This qualitative research process understands that people create their own structured reality (‘the social construction of reality’), based on their past experiences. So, by viewing the way people intentionally live their lives, we’re able to see the experiential meaning behind why they live as they do.
• Narrative research: Narrative research, or narrative inquiry, is where researchers examine the way stories are told by participants, and how they explain their experiences, as a way of explaining the meaning behind their life choices and events. This qualitative research can arise from using journals, conversational stories, autobiographies or letters, as a few narrative research examples. The narrative is subjective to the participant, so we’re able to understand their views from what they’ve documented/spoken.

Qualitative research methods can use structured research instruments for data collection, like:

Surveys for individual views

A survey is a simple-to-create and easy-to-distribute qualitative research method, which helps gather information from large groups of participants quickly. Traditionally, paper-based surveys can now be made online, so costs can stay quite low.

Qualitative research questions tend to be open questions that ask for more information and provide a text box to allow for unconstrained comments.

Examples include:

• Asking participants to keep a written or a video diary for a period of time to document their feelings and thoughts
• In-Home-Usage tests: Buyers use your product for a period of time and report their experience

Surveys for group consensus (Delphi survey)

A Delphi survey may be used as a way to bring together participants and gain a consensus view over several rounds of questions. It differs from traditional surveys where results go to the researcher only. Instead, results go to participants as well, so they can reflect and consider all responses before another round of questions are submitted.

This can be useful to do as it can help researchers see what variance is among the group of participants and see the process of how consensus was reached.

• Asking participants to act as a fake jury for a trial and revealing parts of the case over several rounds to see how opinions change. At the end, the fake jury must make a unanimous decision about the defendant on trial.
• Asking participants to comment on the versions of a product being developed , as the changes are made and their feedback is taken onboard. At the end, participants must decide whether the product is ready to launch .

Semi-structured interviews

Interviews are a great way to connect with participants, though they require time from the research team to set up and conduct, especially if they’re done face-to-face.

Researchers may also have issues connecting with participants in different geographical regions. The researcher uses a set of predefined open-ended questions, though more ad-hoc questions can be asked depending on participant answers.

• Conducting a phone interview with participants to run through their feedback on a product . During the conversation, researchers can go ‘off-script’ and ask more probing questions for clarification or build on the insights.

Focus groups

Participants are brought together into a group, where a particular topic is discussed. It is researcher-led and usually occurs in-person in a mutually accessible location, to allow for easy communication between participants in focus groups.

In focus groups , the researcher uses a set of predefined open-ended questions, though more ad-hoc questions can be asked depending on participant answers.

• Asking participants to do UX tests, which are interface usability tests to show how easily users can complete certain tasks

Direct observation

This is a form of ethnographic research where researchers will observe participants’ behavior in a naturalistic environment. This can be great for understanding the actions in the culture and context of a participant’s setting.

This qualitative research method is prone to researcher bias as it is the researcher that must interpret the actions and reactions of participants. Their findings can be impacted by their own beliefs, values, and inferences.

• Embedding yourself in the location of your buyers to understand how a product would perform against the values and norms of that society

Qualitative data types and category types

Qualitative research methods often deliver information in the following qualitative research data types:

• Written testimonials

Through contextual analysis of the information, researchers can assign participants to category types:

• Social class
• Political alignment
• Most likely to purchase a product
• Their preferred training learning style

Advantages of qualitative research

• Useful for complex situations: Qualitative research on its own is great when dealing with complex issues, however, providing background context using quantitative facts can give a richer and wider understanding of a topic. In these cases, quantitative research may not be enough.
• A window into the ‘why’: Qualitative research can give you a window into the deeper meaning behind a participant’s answer. It can help you uncover the larger ‘why’ that can’t always be seen by analyzing numerical data.
• Can help improve customer experiences: In service industries where customers are crucial, like in private health services, gaining information about a customer’s experience through health research studies can indicate areas where services can be improved.

Disadvantages of qualitative research

• You need to ask the right question: Doing qualitative research may require you to consider what the right question is to uncover the underlying thinking behind a behavior. This may need probing questions to go further, which may suit a focus group or face-to-face interview setting better.
• Results are interpreted: As qualitative research data is written, spoken, and often nuanced, interpreting the data results can be difficult as they come in non-numerical formats. This might make it harder to know if you can accept or reject your hypothesis.
• More bias: There are lower levels of control to qualitative research methods, as they can be subject to biases like confirmation bias, researcher bias, and observation bias. This can have a knock-on effect on the validity and truthfulness of the qualitative research data results.

How to use qualitative research to your business’s advantage?

Qualitative methods help improve your products and marketing in many different ways:

• Understand the emotional connections to your brand
• Identify obstacles to purchase
• Uncover doubts and confusion about your messaging
• Find missing product features
• Improve the usability of your website, app, or chatbot experience
• Learn about how consumers talk about your product
• See how buyers compare your brand to others in the competitive set
• Learn how an organization’s employees evaluate and select vendors

6 steps to conducting good qualitative research

Businesses can benefit from qualitative research by using it to understand the meaning behind data types. There are several steps to this:

• Define your problem or interest area: What do you observe is happening and is it frequent? Identify the data type/s you’re observing.
• Create a hypothesis: Ask yourself what could be the causes for the situation with those qualitative research data types.
• Plan your qualitative research: Use structured qualitative research instruments like surveys, focus groups, or interviews to ask questions that test your hypothesis.
• Data Collection: Collect qualitative research data and understand what your data types are telling you. Once data is collected on different types over long time periods, you can analyze it and give insights into changing attitudes and language patterns.
• Data analysis: Does your information support your hypothesis? (You may need to redo the qualitative research with other variables to see if the results improve)
• Effectively present the qualitative research data: Communicate the results in a clear and concise way to help other people understand the findings.

Qualitative data analysis

Evaluating qualitative research can be tough when there are several analytics platforms to manage and lots of subjective data sources to compare.

Qualtrics provides a number of qualitative research analysis tools, like Text iQ , powered by Qualtrics iQ, provides powerful machine learning and native language processing to help you discover patterns and trends in text.

This also provides you with:

• Sentiment analysis — a technique to help identify the underlying sentiment (say positive, neutral, and/or negative) in qualitative research text responses
• Topic detection/categorisation — this technique is the grouping or bucketing of similar themes that can are relevant for the business & the industry (eg. ‘Food quality’, ‘Staff efficiency’ or ‘Product availability’)

How Qualtrics products can enhance & simplify the qualitative research process

Even in today’s data-obsessed marketplace, qualitative data is valuable – maybe even more so because it helps you establish an authentic human connection to your customers. If qualitative research doesn’t play a role to inform your product and marketing strategy, your decisions aren’t as effective as they could be.

The Qualtrics XM system gives you an all-in-one, integrated solution to help you all the way through conducting qualitative research. From survey creation and data collection to textual analysis and data reporting, it can help all your internal teams gain insights from your subjective and categorical data.

Qualitative methods are catered through templates or advanced survey designs. While you can manually collect data and conduct data analysis in a spreadsheet program, this solution helps you automate the process of qualitative research, saving you time and administration work.

Using computational techniques helps you to avoid human errors, and participant results come in are already incorporated into the analysis in real-time.

Our key tools, Text IQ™ and Driver IQ™ make analyzing subjective and categorical data easy and simple. Choose to highlight key findings based on topic, sentiment, or frequency. The choice is yours.

Some examples of your workspace in action, using drag and drop to create fast data visualizations quickly:

Related resources

Market intelligence 10 min read, marketing insights 11 min read, ethnographic research 11 min read, qualitative vs quantitative research 13 min read, qualitative research questions 11 min read, qualitative research design 12 min read, primary vs secondary research 14 min read, request demo.

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How to prepare a questionnaire for qualitative research

Our guide to market research can be downloaded free of charge

Qualitative research is what we consider the first real technical step of market research. The qualitative questionnaire(also called interview guide) is instrumental for the success of this phase. In this post we explain EXACTLY how to prepare it.

As we’ve explained in other posts , market research is NOT only administrating a survey. It’s much more than that (get an overview of market research tools and techniques on our online guide ).

Today we’d like to discuss what we consider being the very first step when it comes to better understand your market and your future customer: conducting interviews .

Table of contents

Introduction.

• Step 1 : define your topics
• Step 2 : rank your topics
• Step 3 : define the questions
• Our secret tip for framing better questions

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Interviews are just one of many qualitative research tools available to the market researcher. You could also do focus groups, participatory or non-participatory observations. The range is very wide. If you want to know more we recommend you read this  book by D. Silverman who has featured my work in the latest edition of his book. Choosing the right qualitative technique (or the right combination of techniques) is a work in itself. We have prepared a quite complete list of marketing problems you my face with the methodological approaches we recommend.

But whatever you chose to do you should make sure you do it right. Don’t do like most people we met who just ask a few questions, don’t even take the time to write them down and after having interviewed 5 people think they are finished . Qualitative research is more than that. Do it the right way and you’ll be rewarded.

On the funnel below (which represents the 7-step market research approach detailed here ), qualitative market research (to which qualitative interviews belong) is step #5.

Before you even start: the literature review

Preparing an interview guide (or qualitative questionnaire) requires that you master the topic you will cover. In particular you need to do your homework to understand what has already been said, written, researched on the topic. You could look after professional reports to get that knowledge. However, for the sake of quality, we highly recommend you only use academic sources. We have explained all you need to know about desk research . It’s one of our most comprehensive articles written in the last 10 years, so make sure you read it.

We suggest you use Google Scholar to find the latest academic articles on your topic. If you want to conduct qualitative interview about organic food consumption, a search in google scholar will return this.

As you can see I’ve entered “organic food consumption” as keywords and have not used any filters. I already get interesting results and some articles are freely available (I’ve highlighted them in yellow). This means you won’t have to pay to get access to them. Normally most scientific articles can be accessed only if you pay; unless you are a student or a researcher and in that case you can access them through your local library.

STEP 1 : define your topics

Before even starting out, you have to define which topics you want to cover . Two or three topics are the maximum. Don’t try to cover too many. That won’t work. Remember.

If you want to investigate organic food consumption, you need to focus on that. You won’t have time to explore in depth other topics (non-organic food consumption or non-food organic consumption for instance). You really need to dedicate all your energy and all your focus to that topic. Along the way you probably will discuss anyway other topics that touch on your main one.

Your main topic (organic food consumption) will fold into sub-themes. Here are a few examples that come to mind :

• The patterns of organic shopping
• The patterns of organic food consumption
• the reasons behind organic food consumption
• How respondents’ behaviors have changed since they adopted organic food

These sub-themes will come from your literature (that’s why it’s important to do one) and you’ll have to order them in your qualitative questionnaire.

STEP 2 : rank your topics

Now that you topics are defined, you have to rank them. Use the funnel method (hence the image above) and start with the most general topic and then move to more particular ones. This ranking will ensure your interview doesn’t look strange when conducted. It will follow a natural path that will not bother the interviewee.

Just like in a quantitative questionnaire you also need to end your interview with the questions that require the less cognitive energy. If your qualitative interview includes some creative techniques (collage, image ranking, …) do that at the beginning.

From a strategic viewpoint it’s also important not to end with the most important themes. You want your respondents to be in full cognitive power to answer your most important questions.

STEP 3 : define your questions

For each theme you should have a set of questions at your disposal to cover the different possible aspects. Keep this in mind: it is impossible to address one topic (especially when it’s complex) with one question alone. Usually, you’ll need three or more questions. Here again use the funnel technique. Start with a general open question, then with an open-ended one, and finish with a directed question.

Defining and framing the questions is obviously a big factor of success. The good news is that other researchers before you have been faced with the same issues. Other researchers have tried to define and validate what what are called “scales of measure”. Scales are intrinsically quantitative instrument that allow the measurement of a construct. Although they are primarily used for quantitative research, scales offer great insights into which questions to ask. Why not use these scales to define the questions of your qualitative questionnaire too?

Our secret tip for better questions: the book of scales

This is a tip no one will probably give you. You can get access to a book of scales for free (at least partially) and define qualitative questions that will make the difference. Use the table of content to find the construct(s) you need to evaluate and go to the dedicated chapter to see which questions you need to ask. A book of scale is worth 150$ and you’ll get it partially free below.

Here’s the rule you should remember for your next qualitative interview : 3×3=9. You should have no more than 3 themes to address, and address each topic with 3 questions. Eventually 9 questions should be sufficient to conduct the interview. The Art is actually in maintaining a good level of dialogue with the respondent and to make sure the answers provided are the most comprehensive.

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1 August 2017

12 November 2017

But it can be 3×4, right? One main topic with four sub topic? Perception on four areas..

7 January 2019

Very helpful comments. Will use this information in my research.

8 January 2019

You are most welcome. Always happy to help.

6 April 2023

thank you it was very helpful

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

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

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

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

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

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

Table of contents

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

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

Common uses of survey research include:

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

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

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

Populations

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

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

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

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

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

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

There are two main types of survey:

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

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

Questionnaires

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

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

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

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

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

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

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

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

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

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

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

Open-ended vs closed-ended questions

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

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

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

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

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

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

The content of the survey questions

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

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

Phrasing the survey questions

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

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

Ordering the survey questions

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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How to Write Qualitative Research Questions: Types & Examples

Sameer Bhatia

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Sameer Bhatia is the Founder and Chief Executive Officer of ProProfs.com. He believes that software should make you happy and is driven to create a 100-year company that delivers delightfully ... Read more

Sameer Bhatia is the Founder and Chief Executive Officer of ProProfs.com. He believes that software should make you happy and is driven to create a 100-year company that delivers delightfully smart software with awesome support. His favorite word is 'delight,' and he dislikes the term 'customer satisfaction,' as he believes that 'satisfaction' is a low bar and users must get nothing less than a delightful experience at ProProfs. Sameer holds a Masters in Computer Science from the University of Southern California (USC). He lives in Santa Monica with his wife & two daughters. Read less

Market Research Specialist

Emma David, a seasoned market research professional, specializes in employee engagement, survey administration, and data management. Her expertise in leveraging data for informed decisions has positively impacted several brands, enhancing their market position.

Qualitative research questions focus on depth and quality, exploring the “why and how” behind decisions, without relying on statistical tools.

Unlike quantitative research, which aims to collect tangible, measurable data from a broader demographic, qualitative analysis involves smaller, focused datasets, identifying patterns for insights.

The information collected by qualitative surveys can vary from text to images, demanding a deep understanding of the subject, and therefore, crafting precise qualitative research questions is crucial for success.

In this guide, we’ll discuss how to write effective qualitative research questions, explore various types, and highlight characteristics of good qualitative research questions.

Let’s dive in!

What Are Qualitative Research Questions?

Qualitative questions aim to understand the depth and nuances of a phenomenon, focusing on “why” and “how” rather than quantifiable measures.

They explore subjective experiences, perspectives, and behaviors, often using open-ended inquiries to gather rich, descriptive data.

Unlike quantitative questions, which seek numerical data, qualitative questions try to find out meanings, patterns, and underlying processes within a specific context.

These questions are essential for exploring complex issues, generating hypotheses, and gaining deeper insights into human behavior and phenomena.

Here’s an example of a qualitative research question:

“How do you perceive and navigate organizational culture within a tech startup environment?”

This question asks about the respondent’s subjective interpretations and experiences of organizational culture within a specific context, such as a tech startup.

It seeks to uncover insights into the values, norms, and practices that shape workplace dynamics and employee behaviors, providing qualitative data for analysis and understanding.

When Should We Use Qualitative Research Questions?

Qualitative research questions typically aim to open up conversations, encourage detailed narratives, and foster a deep understanding of the subject matter. Here are some scenarios they are best suited for:

• Exploring Complex Phenomena : When the research topic involves understanding complex processes, behaviors, or interactions that cannot be quantified easily, qualitative questions help delve into these intricate details.
• Understanding Contexts and Cultures : To grasp the nuances of different social contexts, cultures, or subcultures, qualitative research questions allow for an in-depth exploration of these environments and how they influence individuals and groups.
• Exploring Perceptions and Experiences : When the aim is to understand people’s perceptions, experiences, or feelings about a particular subject, qualitative questions facilitate capturing the depth and variety of these perspectives.
• Developing Concepts or Theories : In the early stages of research, where concepts or theories are not yet well-developed, qualitative questions can help generate hypotheses, identify variables, and develop theoretical frameworks based on observations and interpretations.
• Investigating Processes : To understand how processes unfold over time and the factors that influence these processes, qualitative questions are useful for capturing the dynamics and complexities involved.
• Seeking to Understand Change : When researching how individuals or groups experience change, adapt to new circumstances, or make decisions, qualitative research questions can provide insights into the motivations, challenges, and strategies involved.
• Studying Phenomena Not Easily Quantified : For phenomena that are not easily captured through quantitative measures, such as emotions, beliefs, or motivations, qualitative questions can probe these abstract concepts more effectively.
• Addressing Sensitive or Taboo Topics : In studies where topics may be sensitive, controversial, or taboo, qualitative research questions allow for a respectful and empathetic exploration of these subjects, providing space for participants to share their experiences in their own words.

How to Write Qualitative Research Questions?

Read this guide to learn how you can craft well-thought-out qualitative research questions:

1. Begin with Your Research Goals

The first step in formulating qualitative research questions is to have a clear understanding of what you aim to discover or understand through your research. There are two types of qualitative questionnaires or research – Ontological and Epistemological.

Finding out the nature of your research influences all aspects of your research design, including the formulation of research questions.

Subsequently:

• Identify your main objective : Consider the broader context of your study. Are you trying to explore a phenomenon, understand a process, or interpret the meanings behind behaviors? Your main objective should guide the formulation of your questions, ensuring they are aligned with what you seek to achieve.
• Focus on the ‘how’ and ‘why’ : Qualitative research is inherently exploratory and aims to understand the nuances of human behavior and experience. Starting your questions with “how” or “why” encourages a deeper investigation into the motivations, processes, and contexts underlying the subject matter. This approach facilitates an open-ended exploration, allowing participants to provide rich, detailed responses that illuminate their perspectives and experiences.

Take a quick look at the following visual for a better understanding:

So, if you are doing Ontological research, ensure that the questions focus on the “what” aspects of reality (the premise of your research) and opt for the nature of the knowledge for Epistemological research.

2. Choose the Right Structure

The structure of your research questions significantly impacts the depth and quality of data you collect. Opting for an open-ended format allows respondents the flexibility to express themselves freely, providing insights that pre-defined answers might miss.

• Open-ended format : These questions do not constrain respondents to a set of predetermined answers, unlike closed-ended questions. By allowing participants to articulate their thoughts in their own words, you can uncover nuances and complexities in their responses that might otherwise be overlooked.
• Avoid yes/no questions : Yes/no questions tend to limit the depth of responses. While they might be useful for gathering straightforward factual information, they are not conducive to exploring the depths and nuances that qualitative research seeks to uncover. Encouraging participants to elaborate on their experiences and perspectives leads to richer, more informative data.

For example, take a look at some qualitative questions examples shown in the following image:

3. Be Clear and Specific

Clarity and specificity in your questions are crucial to ensure that participants understand what is being asked and that their responses are relevant to your research objectives.

• Use clear language : Use straightforward, understandable language in your questions. Avoid jargon, acronyms, or overly technical terms that might confuse participants or lead to misinterpretation. The goal is to make your questions accessible to everyone involved in your study.
• Be specific : While maintaining the open-ended nature of qualitative questions, it’s important to narrow down your focus to specific aspects of the phenomenon you’re studying. This specificity helps guide participants’ responses and ensures that the data you collect directly relates to your research objectives.

4. Ensure Relevance and Feasibility

Each question should be carefully considered for its relevance to your research goals and its feasibility, given the constraints of your study.

• Relevance : Questions should be crafted to address the core objectives of your research directly. They should probe areas that are essential to understanding the phenomenon under investigation and should align with your theoretical framework or literature review findings.
• Feasibility : Consider the practical aspects of your research, including the time available for data collection and analysis, resources, and access to participants. Questions should be designed to elicit meaningful responses within the constraints of your study, ensuring that you can gather and analyze data effectively.

5. Focus on a Single Concept or Theme per Question

To ensure clarity and depth, each question should concentrate on a single idea or theme. However, if your main qualitative research question is tough to understand or has a complex structure, you can create sub-questions in limited numbers and with a “ladder structure”.

This will help your respondents understand the overall research objective in mind, and your research can be executed in a better manner.

For example, suppose your main question is – “What is the current state of illiteracy in your state?”

Then, you can create the following subquestions: 

“How does illiteracy block progress in your state?”

“How would you best describe the feelings you have about illiteracy in your state?”

For an even better understanding, you can see the various examples of qualitative research questions in the following image:

Types of Qualitative Research Questions With Examples

Qualitative survey questions primarily focus on a specific group of respondents that are participating in case studies, surveys, ethnography studies, etc., rather than numbers or statistics.

As a result, the questions are mostly open-ended and can be subdivided into the following types as discussed below:

1. Descriptive Questions

Descriptive research questions aim to detail the “what” of a phenomenon, providing a comprehensive overview of the context, individuals, or situations under study. These questions are foundational, helping to establish a baseline understanding of the research topic.

• What are the daily experiences of teachers in urban elementary schools?
• What strategies do small businesses employ to adapt to rapid technological changes?
• How do young adults describe their transition from college to the workforce?
• What are the coping mechanisms of families with members suffering from chronic illnesses?
• How do community leaders perceive the impact of gentrification in their neighborhoods?

2. Interpretive Questions

Interpretive questions seek to understand the “how” and “why” behind a phenomenon, focusing on the meanings people attach to their experiences. These questions delve into the subjective interpretations and perceptions of participants.

• How do survivors of natural disasters interpret their experiences of recovery and rebuilding?
• Why do individuals engage in voluntary work within their communities?
• How do parents interpret and navigate the challenges of remote schooling for their children?
• Why do consumers prefer local products over global brands in certain markets?
• How do artists interpret the influence of digital media on traditional art forms?

3. Comparative Questions

Comparative research questions are designed to explore differences and similarities between groups, settings, or time periods. These questions can help to highlight the impact of specific variables on the phenomenon under study.

• How do the strategies for managing work-life balance compare between remote and office workers?
• What are the differences in consumer behavior towards sustainable products in urban versus rural areas?
• How do parenting styles in single-parent households compare to those in dual-parent households?
• What are the similarities and differences in leadership styles across different cultures?
• How has the perception of online privacy changed among teenagers over the past decade?

4. Process-oriented Questions

These questions focus on understanding the processes or sequences of events over time. They aim to uncover the “how” of a phenomenon, tracing the development, changes, or evolution of specific situations or behaviors.

• How do non-profit organizations develop and implement community outreach programs?
• What is the process of decision-making in high-stakes business environments?
• How do individuals navigate the process of career transition after significant industry changes?
• What are the stages of adaptation for immigrants in a new country?
• How do social movements evolve from inception to national recognition?

5. Evaluative Questions

Evaluative questions aim to assess the effectiveness, value, or impact of a program, policy, or phenomenon. These questions are critical for understanding the outcomes and implications of various initiatives or situations.

• How effective are online therapy sessions compared to in-person sessions in treating anxiety?
• What is the impact of community gardening programs on neighborhood cohesion?
• How do participants evaluate the outcomes of leadership training programs in their professional development?
• What are the perceived benefits and drawbacks of telecommuting for employees and employers?
• How do residents evaluate the effectiveness of local government policies on waste management?

6. One-on-One Questions

The one-on-one questions are asked to a single person and can be thought of as individual interviews that you can conduct online via phone and video chat as well.

The main aim of such questions is to ask your customers or people in the focus group a series of questions about their purchase motivations. These questions might also come with follow-ups, and if your customers respond with some interesting fact or detail, dig deeper and explore the findings as much as you want.

• What makes you happy in regard to [your research topic]?
• If I could make a wish of yours come true, what do you desire the most?
• What do you still find hard to come to terms with?
• Have you bought [your product] before?
• If so, what was your initial motivation behind the purchase?

7. Exploratory Questions

These questions are designed to enhance your understanding of a particular topic. However, while asking exploratory questions, you must ensure that there are no preconceived notions or biases to it. The more transparent and bias-free your questions are, the better and fair results you will get.

• What is the effect of personal smart devices on today’s youth?
• Do you feel that smart devices have positively or negatively impacted you?
• How do your kids spend their weekends?
• What do you do on a typical weekend morning?

8. Predictive Questions

The predictive questions are used for qualitative research that is focused on the future outcomes of an action or a series of actions. So, you will be using past information to predict the reactions of respondents to hypothetical events that might or might not happen in the future.

These questions come in extremely handy for identifying your customers’ current brand expectations, pain points, and purchase motivation.

• Are you more likely to buy a product when a celebrity promotes it?
• Would you ever try a new product because one of your favorite celebs claims that it actually worked for them?
• Would people in your neighborhood enjoy a park with rides and exercise options?
• How often would you go to a park with your kids if it had free rides?

9. Focus Groups

These questions are mostly asked in person to the customer or respondent groups. The in-person nature of these surveys or studies ensures that the group members get a safe and comfortable environment to express their thoughts and feelings about your brand or services.

• How would you describe your ease of using our product?
• How well do you think you were able to do this task before you started using our product?
• What do you like about our promotional campaigns?
• How well do you think our ads convey the meaning?

10. In-Home Videos

Collecting video feedback from customers in their comfortable, natural settings offers a unique perspective. At home, customers are more relaxed and less concerned about their mannerisms, posture, and choice of words when responding.

This approach is partly why Vogue’s 73 Questions Series is highly popular among celebrities and viewers alike. In-home videos provide insights into customers in a relaxed environment, encouraging them to be honest and share genuine experiences.

• What was your first reaction when you used our product for the first time?
• How well do you think our product performed compared to your expectations?
• What was your worst experience with our product?
• What made you switch to our brand?

11. Online Focus Groups

Online focus groups mirror the traditional, in-person format but are conducted virtually, offering a more cost-effective and efficient approach to gathering data. This digital format extends your reach and allows a rapid collection of responses from a broader audience through online platforms.

You can utilize social media and other digital forums to create communities of respondents and initiate meaningful discussions. Once you have them started, you can simply observe the exchange of thoughts and gather massive amounts of interesting insights!

• What do you like best about our product?
• How familiar are you with this particular service or product we offer?
• What are your concerns with our product?
• What changes can we make to make our product better?

Ask the Right Qualitative Research Questions for Meaningful Insights From Your Respondents

Watch: How to Create a Survey Using ProProfs Survey Maker

By now, you might have realized that manually creating a list of qualitative research questions is a daunting task. Keeping numerous considerations in mind, it’s easy to run out of ideas while crafting qualitative survey questions.

However, investing in smart survey tools, like ProProfs Survey Maker, can significantly streamline this process, allowing you to create various types of surveys in minutes.

With this survey tool , you can generate forms, NPS surveys , tests, quizzes, and assessments.

It’s also useful for conducting polls, sidebar surveys, and in-app surveys. Offering over 100 templates and more than 1,000,000 ready-to-use examples of phenomenological research questions, this software simplifies the task immensely.

Equipped with the right tools and the professional tips shared here, you’re well-prepared to conduct thorough research studies and obtain valuable insights that drive impactful results.

Frequently Asked Questions

1. how do you choose qualitative research questions.

To choose qualitative research questions, identify your main research goal, focus on exploring ‘how’ and ‘why’ aspects, ensure questions are open-ended, and align them with your theoretical framework and methodology.

2. Why are good qualitative research questions important?

Good qualitative research questions are important because they guide the research focus, enable the exploration of depth and complexity, and facilitate the gathering of rich, detailed insights into human experiences and behaviors.

About the author

Emma David is a seasoned market research professional with 8+ years of experience. Having kick-started her journey in research, she has developed rich expertise in employee engagement, survey creation and administration, and data management. Emma believes in the power of data to shape business performance positively. She continues to help brands and businesses make strategic decisions and improve their market standing through her understanding of research methodologies.

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Understanding and Evaluating Survey Research

A variety of methodologic approaches exist for individuals interested in conducting research. Selection of a research approach depends on a number of factors, including the purpose of the research, the type of research questions to be answered, and the availability of resources. The purpose of this article is to describe survey research as one approach to the conduct of research so that the reader can critically evaluate the appropriateness of the conclusions from studies employing survey research.

SURVEY RESEARCH

Survey research is defined as "the collection of information from a sample of individuals through their responses to questions" ( Check & Schutt, 2012, p. 160 ). This type of research allows for a variety of methods to recruit participants, collect data, and utilize various methods of instrumentation. Survey research can use quantitative research strategies (e.g., using questionnaires with numerically rated items), qualitative research strategies (e.g., using open-ended questions), or both strategies (i.e., mixed methods). As it is often used to describe and explore human behavior, surveys are therefore frequently used in social and psychological research ( Singleton & Straits, 2009 ).

Information has been obtained from individuals and groups through the use of survey research for decades. It can range from asking a few targeted questions of individuals on a street corner to obtain information related to behaviors and preferences, to a more rigorous study using multiple valid and reliable instruments. Common examples of less rigorous surveys include marketing or political surveys of consumer patterns and public opinion polls.

Survey research has historically included large population-based data collection. The primary purpose of this type of survey research was to obtain information describing characteristics of a large sample of individuals of interest relatively quickly. Large census surveys obtaining information reflecting demographic and personal characteristics and consumer feedback surveys are prime examples. These surveys were often provided through the mail and were intended to describe demographic characteristics of individuals or obtain opinions on which to base programs or products for a population or group.

More recently, survey research has developed into a rigorous approach to research, with scientifically tested strategies detailing who to include (representative sample), what and how to distribute (survey method), and when to initiate the survey and follow up with nonresponders (reducing nonresponse error), in order to ensure a high-quality research process and outcome. Currently, the term "survey" can reflect a range of research aims, sampling and recruitment strategies, data collection instruments, and methods of survey administration.

Given this range of options in the conduct of survey research, it is imperative for the consumer/reader of survey research to understand the potential for bias in survey research as well as the tested techniques for reducing bias, in order to draw appropriate conclusions about the information reported in this manner. Common types of error in research, along with the sources of error and strategies for reducing error as described throughout this article, are summarized in the Table .

Sources of Error in Survey Research and Strategies to Reduce Error

The goal of sampling strategies in survey research is to obtain a sufficient sample that is representative of the population of interest. It is often not feasible to collect data from an entire population of interest (e.g., all individuals with lung cancer); therefore, a subset of the population or sample is used to estimate the population responses (e.g., individuals with lung cancer currently receiving treatment). A large random sample increases the likelihood that the responses from the sample will accurately reflect the entire population. In order to accurately draw conclusions about the population, the sample must include individuals with characteristics similar to the population.

It is therefore necessary to correctly identify the population of interest (e.g., individuals with lung cancer currently receiving treatment vs. all individuals with lung cancer). The sample will ideally include individuals who reflect the intended population in terms of all characteristics of the population (e.g., sex, socioeconomic characteristics, symptom experience) and contain a similar distribution of individuals with those characteristics. As discussed by Mady Stovall beginning on page 162, Fujimori et al. ( 2014 ), for example, were interested in the population of oncologists. The authors obtained a sample of oncologists from two hospitals in Japan. These participants may or may not have similar characteristics to all oncologists in Japan.

Participant recruitment strategies can affect the adequacy and representativeness of the sample obtained. Using diverse recruitment strategies can help improve the size of the sample and help ensure adequate coverage of the intended population. For example, if a survey researcher intends to obtain a sample of individuals with breast cancer representative of all individuals with breast cancer in the United States, the researcher would want to use recruitment strategies that would recruit both women and men, individuals from rural and urban settings, individuals receiving and not receiving active treatment, and so on. Because of the difficulty in obtaining samples representative of a large population, researchers may focus the population of interest to a subset of individuals (e.g., women with stage III or IV breast cancer). Large census surveys require extremely large samples to adequately represent the characteristics of the population because they are intended to represent the entire population.

DATA COLLECTION METHODS

Survey research may use a variety of data collection methods with the most common being questionnaires and interviews. Questionnaires may be self-administered or administered by a professional, may be administered individually or in a group, and typically include a series of items reflecting the research aims. Questionnaires may include demographic questions in addition to valid and reliable research instruments ( Costanzo, Stawski, Ryff, Coe, & Almeida, 2012 ; DuBenske et al., 2014 ; Ponto, Ellington, Mellon, & Beck, 2010 ). It is helpful to the reader when authors describe the contents of the survey questionnaire so that the reader can interpret and evaluate the potential for errors of validity (e.g., items or instruments that do not measure what they are intended to measure) and reliability (e.g., items or instruments that do not measure a construct consistently). Helpful examples of articles that describe the survey instruments exist in the literature ( Buerhaus et al., 2012 ).

Questionnaires may be in paper form and mailed to participants, delivered in an electronic format via email or an Internet-based program such as SurveyMonkey, or a combination of both, giving the participant the option to choose which method is preferred ( Ponto et al., 2010 ). Using a combination of methods of survey administration can help to ensure better sample coverage (i.e., all individuals in the population having a chance of inclusion in the sample) therefore reducing coverage error ( Dillman, Smyth, & Christian, 2014 ; Singleton & Straits, 2009 ). For example, if a researcher were to only use an Internet-delivered questionnaire, individuals without access to a computer would be excluded from participation. Self-administered mailed, group, or Internet-based questionnaires are relatively low cost and practical for a large sample ( Check & Schutt, 2012 ).

Dillman et al. ( 2014 ) have described and tested a tailored design method for survey research. Improving the visual appeal and graphics of surveys by using a font size appropriate for the respondents, ordering items logically without creating unintended response bias, and arranging items clearly on each page can increase the response rate to electronic questionnaires. Attending to these and other issues in electronic questionnaires can help reduce measurement error (i.e., lack of validity or reliability) and help ensure a better response rate.

Conducting interviews is another approach to data collection used in survey research. Interviews may be conducted by phone, computer, or in person and have the benefit of visually identifying the nonverbal response(s) of the interviewee and subsequently being able to clarify the intended question. An interviewer can use probing comments to obtain more information about a question or topic and can request clarification of an unclear response ( Singleton & Straits, 2009 ). Interviews can be costly and time intensive, and therefore are relatively impractical for large samples.

Some authors advocate for using mixed methods for survey research when no one method is adequate to address the planned research aims, to reduce the potential for measurement and non-response error, and to better tailor the study methods to the intended sample ( Dillman et al., 2014 ; Singleton & Straits, 2009 ). For example, a mixed methods survey research approach may begin with distributing a questionnaire and following up with telephone interviews to clarify unclear survey responses ( Singleton & Straits, 2009 ). Mixed methods might also be used when visual or auditory deficits preclude an individual from completing a questionnaire or participating in an interview.

FUJIMORI ET AL.: SURVEY RESEARCH

Fujimori et al. ( 2014 ) described the use of survey research in a study of the effect of communication skills training for oncologists on oncologist and patient outcomes (e.g., oncologist’s performance and confidence and patient’s distress, satisfaction, and trust). A sample of 30 oncologists from two hospitals was obtained and though the authors provided a power analysis concluding an adequate number of oncologist participants to detect differences between baseline and follow-up scores, the conclusions of the study may not be generalizable to a broader population of oncologists. Oncologists were randomized to either an intervention group (i.e., communication skills training) or a control group (i.e., no training).

Fujimori et al. ( 2014 ) chose a quantitative approach to collect data from oncologist and patient participants regarding the study outcome variables. Self-report numeric ratings were used to measure oncologist confidence and patient distress, satisfaction, and trust. Oncologist confidence was measured using two instruments each using 10-point Likert rating scales. The Hospital Anxiety and Depression Scale (HADS) was used to measure patient distress and has demonstrated validity and reliability in a number of populations including individuals with cancer ( Bjelland, Dahl, Haug, & Neckelmann, 2002 ). Patient satisfaction and trust were measured using 0 to 10 numeric rating scales. Numeric observer ratings were used to measure oncologist performance of communication skills based on a videotaped interaction with a standardized patient. Participants completed the same questionnaires at baseline and follow-up.

The authors clearly describe what data were collected from all participants. Providing additional information about the manner in which questionnaires were distributed (i.e., electronic, mail), the setting in which data were collected (e.g., home, clinic), and the design of the survey instruments (e.g., visual appeal, format, content, arrangement of items) would assist the reader in drawing conclusions about the potential for measurement and nonresponse error. The authors describe conducting a follow-up phone call or mail inquiry for nonresponders, using the Dillman et al. ( 2014 ) tailored design for survey research follow-up may have reduced nonresponse error.

CONCLUSIONS

Survey research is a useful and legitimate approach to research that has clear benefits in helping to describe and explore variables and constructs of interest. Survey research, like all research, has the potential for a variety of sources of error, but several strategies exist to reduce the potential for error. Advanced practitioners aware of the potential sources of error and strategies to improve survey research can better determine how and whether the conclusions from a survey research study apply to practice.

The author has no potential conflicts of interest to disclose.

2024 Theses Doctoral

Artificial Intelligence vs. Human Coaches: A Mixed Methods Randomized Controlled Experiment on Client Experiences and Outcomes

Barger, Amber

The rise of artificial intelligence (AI) challenges us to explore whether human-to-human relationships can extend to AI, potentially reshaping the future of coaching. The purpose of this study was to examine client perceptions of being coached by a simulated AI coach, who was embodied as a vocally conversational live-motion avatar, compared to client perceptions of a human coach. It explored if and how client ratings of coaching process measures and outcome measures aligned between the two coach treatments. In this mixed methods randomized controlled trial (RCT), 81 graduate students enrolled in the study and identified a personally relevant goal to pursue. The study deployed an alternative-treatments between-subjects design, with one-third of participants receiving coaching from simulated AI coaches, another third engaging with seasoned human coaches, and the rest forming the control group. Both treatment groups had one 60-minute session guided by the CLEAR (contract, listen, explore, action, review) coaching model to support each person to gain clarity about their goal and identify specific behaviors that could help each make progress towards their goal. Quantitative data were captured through three surveys and qualitative input was captured through open-ended survey questions and 27 debrief interviews. The study utilized a Wizard of Oz technique from human-computer interaction research, ingeniously designed to sidestep the rapid obsolescence of technology by simulating an advanced AI coaching experience where participants unknowingly interacted with professional human coaches, enabling the assessment of responses to AI coaching in the absence of fully developed autonomous AI systems. The aim was to glean insights into client reactions to a future, fully autonomous AI with the expert capabilities of a human coach. Contrary to expectations from previous literature, participants did not rate professional human coaches higher than simulated AI coaches in terms of working alliance, session value, or outcomes, which included self-rated competence and goal achievement. In fact, both coached groups made significant progress compared to the control group, with participants convincingly engaging with their respective coaches, as confirmed by a novel believability index. The findings challenge prevailing assumptions about human uniqueness in relation to technology. The rapid advancement of AI suggests a revolutionary shift in coaching, where AI could take on a central and surprisingly effective role, redefining what we thought only human coaches could do and reshaping their role in the age of AI.

• Adult education
• Artificial intelligence--Educational applications
• Graduate students
• Educational technology--Evaluation
• Education, Higher--Technological innovations
• Education, Higher--Effect of technological innovations on

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