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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   
• Hancock, B., Ockleford, E., & Windridge, K. (2009). An introduction to qualitative research. NHS. https://d1wqtxts1xzle7.cloudfront.net/54784339/5_Introduction-to-qualitative-research-2009-libre.pdf?1508678366=&response-content-disposition=inline%3B+filename%3DAn_Introduction_to_Qualitative_Research.pdf&Expires=1712109111&Signature=eSYTDM~wQmdcdPvCxduzVFFU0jHQM-m3Fb8UlSsrSV5jZoVR3xXNoj5V5kL5oQSKqNlkqT-wr6GUF0GtvECzSKS4~toeArp3QEY1jWGmFDVhj~JqQaSvwl8T9BFuzOTpp5QsGGSRFomM7rVIkuE4tJP1TyZGGnGvngFO~-H3mIg7gCM~j-KHqNREOueQqPeIhMSOxTBnUxGWtkrGmM4d~Ab3YVP-ZfQzW9ZchO~-uxcViqWjdt0o8Jo3l3JAv1h0MgP5ssXGIOjOmwQpUClA0d4vIkbD9whyiRWC9TdmcdF1lrc4i1MGB7DQTvQuPb9UCveMNMV3Cxjz-oAtbQMCXQ__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA   
• 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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Writing survey questions.

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

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

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

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

Question development

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

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

Measuring change over time

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

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

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

Open- and closed-ended questions

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

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

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

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

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

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

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

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

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

Question wording

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

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

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

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

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

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

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

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

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

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

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

Question order

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

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

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

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

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

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

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

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

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

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

U.S. Surveys

Other research methods.

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

Qualitative Research Questions: Gain Powerful Insights + 25 Examples

We review the basics of qualitative research questions, including their key components, how to craft them effectively, & 25 example questions.

Einstein was many things—a physicist, a philosopher, and, undoubtedly, a mastermind. He also had an incredible way with words. His quote, "Everything that can be counted does not necessarily count; everything that counts cannot necessarily be counted," is particularly poignant when it comes to research. 

Some inquiries call for a quantitative approach, for counting and measuring data in order to arrive at general conclusions. Other investigations, like qualitative research, rely on deep exploration and understanding of individual cases in order to develop a greater understanding of the whole. That’s what we’re going to focus on today.

Qualitative research questions focus on the "how" and "why" of things, rather than the "what". They ask about people's experiences and perceptions , and can be used to explore a wide range of topics.

The following article will discuss the basics of qualitative research questions, including their key components, and how to craft them effectively. You'll also find 25 examples of effective qualitative research questions you can use as inspiration for your own studies.

Let’s get started!

What are qualitative research questions, and when are they used?

When researchers set out to conduct a study on a certain topic, their research is chiefly directed by an overarching question . This question provides focus for the study and helps determine what kind of data will be collected.

By starting with a question, we gain parameters and objectives for our line of research. What are we studying? For what purpose? How will we know when we’ve achieved our goals?

Of course, some of these questions can be described as quantitative in nature. When a research question is quantitative, it usually seeks to measure or calculate something in a systematic way.

For example:

• How many people in our town use the library?
• What is the average income of families in our city?
• How much does the average person weigh?

Other research questions, however—and the ones we will be focusing on in this article—are qualitative in nature. Qualitative research questions are open-ended and seek to explore a given topic in-depth.

According to the Australian & New Zealand Journal of Psychiatry , “Qualitative research aims to address questions concerned with developing an understanding of the meaning and experience dimensions of humans’ lives and social worlds.”

This type of research can be used to gain a better understanding of people’s thoughts, feelings and experiences by “addressing questions beyond ‘what works’, towards ‘what works for whom when, how and why, and focusing on intervention improvement rather than accreditation,” states one paper in Neurological Research and Practice .

Qualitative questions often produce rich data that can help researchers develop hypotheses for further quantitative study.

• What are people’s thoughts on the new library?
• How does it feel to be a first-generation student at our school?
• How do people feel about the changes taking place in our town?

As stated by a paper in Human Reproduction , “...‘qualitative’ methods are used to answer questions about experience, meaning, and perspective, most often from the standpoint of the participant. These data are usually not amenable to counting or measuring.”

Both quantitative and qualitative questions have their uses; in fact, they often complement each other. A well-designed research study will include a mix of both types of questions in order to gain a fuller understanding of the topic at hand.

If you would like to recruit unlimited participants for qualitative research for free and only pay for the interview you conduct, try using Respondent  today. 

Crafting qualitative research questions for powerful insights

Now that we have a basic understanding of what qualitative research questions are and when they are used, let’s take a look at how you can begin crafting your own.

According to a study in the International Journal of Qualitative Studies in Education, there is a certain process researchers should follow when crafting their questions, which we’ll explore in more depth.

1. Beginning the process 

Start with a point of interest or curiosity, and pose a draft question or ‘self-question’. What do you want to know about the topic at hand? What is your specific curiosity? You may find it helpful to begin by writing several questions.

For example, if you’re interested in understanding how your customer base feels about a recent change to your product, you might ask: 

• What made you decide to try the new product?
• How do you feel about the change?
• What do you think of the new design/functionality?
• What benefits do you see in the change?

2. Create one overarching, guiding question 

At this point, narrow down the draft questions into one specific question. “Sometimes, these broader research questions are not stated as questions, but rather as goals for the study.”

As an example of this, you might narrow down these three questions: 

into the following question: 

• What are our customers’ thoughts on the recent change to our product?

3. Theoretical framing 

As you read the relevant literature and apply theory to your research, the question should be altered to achieve better outcomes. Experts agree that pursuing a qualitative line of inquiry should open up the possibility for questioning your original theories and altering the conceptual framework with which the research began.

If we continue with the current example, it’s possible you may uncover new data that informs your research and changes your question. For instance, you may discover that customers’ feelings about the change are not just a reaction to the change itself, but also to how it was implemented. In this case, your question would need to reflect this new information: 

• How did customers react to the process of the change, as well as the change itself?

4. Ethical considerations 

A study in the International Journal of Qualitative Studies in Education stresses that ethics are “a central issue when a researcher proposes to study the lives of others, especially marginalized populations.” Consider how your question or inquiry will affect the people it relates to—their lives and their safety. Shape your question to avoid physical, emotional, or mental upset for the focus group.

In analyzing your question from this perspective, if you feel that it may cause harm, you should consider changing the question or ending your research project. Perhaps you’ve discovered that your question encourages harmful or invasive questioning, in which case you should reformulate it.

5. Writing the question 

The actual process of writing the question comes only after considering the above points. The purpose of crafting your research questions is to delve into what your study is specifically about” Remember that qualitative research questions are not trying to find the cause of an effect, but rather to explore the effect itself.

Your questions should be clear, concise, and understandable to those outside of your field. In addition, they should generate rich data. The questions you choose will also depend on the type of research you are conducting: 

• If you’re doing a phenomenological study, your questions might be open-ended, in order to allow participants to share their experiences in their own words.
• If you’re doing a grounded-theory study, your questions might be focused on generating a list of categories or themes.
• If you’re doing ethnography, your questions might be about understanding the culture you’re studying.

Whenyou have well-written questions, it is much easier to develop your research design and collect data that accurately reflects your inquiry.

In writing your questions, it may help you to refer to this simple flowchart process for constructing questions:

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25 examples of expertly crafted qualitative research questions

It's easy enough to cover the theory of writing a qualitative research question, but sometimes it's best if you can see the process in practice. In this section, we'll list 25 examples of B2B and B2C-related qualitative questions.

Let's begin with five questions. We'll show you the question, explain why it's considered qualitative, and then give you an example of how it can be used in research.

1. What is the customer's perception of our company's brand?

Qualitative research questions are often open-ended and invite respondents to share their thoughts and feelings on a subject. This question is qualitative because it seeks customer feedback on the company's brand. 

This question can be used in research to understand how customers feel about the company's branding, what they like and don't like about it, and whether they would recommend it to others.

2. Why do customers buy our product?

This question is also qualitative because it seeks to understand the customer's motivations for purchasing a product. It can be used in research to identify the reasons  customers buy a certain product, what needs or desires the product fulfills for them, and how they feel about the purchase after using the product.

3. How do our customers interact with our products?

Again, this question is qualitative because it seeks to understand customer behavior. In this case, it can be used in research to see how customers use the product, how they interact with it, and what emotions or thoughts the product evokes in them.

4. What are our customers' biggest frustrations with our products?

By seeking to understand customer frustrations, this question is qualitative and can provide valuable insights. It can be used in research to help identify areas in which the company needs to make improvements with its products.

5. How do our customers feel about our customer service?

Rather than asking why customers like or dislike something, this question asks how they feel. This qualitative question can provide insights into customer satisfaction or dissatisfaction with a company. 

This type of question can be used in research to understand what customers think of the company's customer service and whether they feel it meets their needs.

20 more examples to refer to when writing your question

Now that you’re aware of what makes certain questions qualitative, let's move into 20 more examples of qualitative research questions:

• How do your customers react when updates are made to your app interface?
• How do customers feel when they complete their purchase through your ecommerce site?
• What are your customers' main frustrations with your service?
• How do people feel about the quality of your products compared to those of your competitors?
• What motivates customers to refer their friends and family members to your product or service?
• What are the main benefits your customers receive from using your product or service?
• How do people feel when they finish a purchase on your website?
• What are the main motivations behind customer loyalty to your brand?
• How does your app make people feel emotionally?
• For younger generations using your app, how does it make them feel about themselves?
• What reputation do people associate with your brand?
• How inclusive do people find your app?
• In what ways are your customers' experiences unique to them?
• What are the main areas of improvement your customers would like to see in your product or service?
• How do people feel about their interactions with your tech team?
• What are the top five reasons people use your online marketplace?
• How does using your app make people feel in terms of connectedness?
• What emotions do people experience when they're using your product or service?
• Aside from the features of your product, what else about it attracts customers?
• How does your company culture make people feel?

As you can see, these kinds of questions are completely open-ended. In a way, they allow the research and discoveries made along the way to direct the research. The questions are merely a starting point from which to explore.

This video offers tips on how to write good qualitative research questions, produced by Qualitative Research Expert, Kimberly Baker.

Wrap-up: crafting your own qualitative research questions.

Over the course of this article, we've explored what qualitative research questions are, why they matter, and how they should be written. Hopefully you now have a clear understanding of how to craft your own.

Remember, qualitative research questions should always be designed to explore a certain experience or phenomena in-depth, in order to generate powerful insights. As you write your questions, be sure to keep the following in mind:

• Are you being inclusive of all relevant perspectives?
• Are your questions specific enough to generate clear answers?
• Will your questions allow for an in-depth exploration of the topic at hand?
• Do the questions reflect your research goals and objectives?

If you can answer "yes" to all of the questions above, and you've followed the tips for writing qualitative research questions we shared in this article, then you're well on your way to crafting powerful queries that will yield valuable insights.

Download Free E-Book

Asking the right questions in the right way is the key to research success. That’s true for not just the discussion guide but for every step of a research project. Following are 100+ questions that will take you from defining your research objective through  screening and participant discussions.

Fill out the form below to access free e-book! 

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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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How to use and assess qualitative research methods

Loraine busetto.

1 Department of Neurology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany

Wolfgang Wick

2 Clinical Cooperation Unit Neuro-Oncology, German Cancer Research Center, Heidelberg, Germany

Christoph Gumbinger

Associated data.

Not applicable.

This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions, and focussing on intervention improvement. The most common methods of data collection are document study, (non-) participant observations, semi-structured interviews and focus groups. For data analysis, field-notes and audio-recordings are transcribed into protocols and transcripts, and coded using qualitative data management software. Criteria such as checklists, reflexivity, sampling strategies, piloting, co-coding, member-checking and stakeholder involvement can be used to enhance and assess the quality of the research conducted. Using qualitative in addition to quantitative designs will equip us with better tools to address a greater range of research problems, and to fill in blind spots in current neurological research and practice.

The aim of this paper is to provide an overview of qualitative research methods, including hands-on information on how they can be used, reported and assessed. This article is intended for beginning qualitative researchers in the health sciences as well as experienced quantitative researchers who wish to broaden their understanding of qualitative research.

What is qualitative research?

Qualitative research is defined as “the study of the nature of phenomena”, including “their quality, different manifestations, the context in which they appear or the perspectives from which they can be perceived” , but excluding “their range, frequency and place in an objectively determined chain of cause and effect” [ 1 ]. This formal definition can be complemented with a more pragmatic rule of thumb: qualitative research generally includes data in form of words rather than numbers [ 2 ].

Why conduct qualitative research?

Because some research questions cannot be answered using (only) quantitative methods. For example, one Australian study addressed the issue of why patients from Aboriginal communities often present late or not at all to specialist services offered by tertiary care hospitals. Using qualitative interviews with patients and staff, it found one of the most significant access barriers to be transportation problems, including some towns and communities simply not having a bus service to the hospital [ 3 ]. A quantitative study could have measured the number of patients over time or even looked at possible explanatory factors – but only those previously known or suspected to be of relevance. To discover reasons for observed patterns, especially the invisible or surprising ones, qualitative designs are needed.

While qualitative research is common in other fields, it is still relatively underrepresented in health services research. The latter field is more traditionally rooted in the evidence-based-medicine paradigm, as seen in " research that involves testing the effectiveness of various strategies to achieve changes in clinical practice, preferably applying randomised controlled trial study designs (...) " [ 4 ]. This focus on quantitative research and specifically randomised controlled trials (RCT) is visible in the idea of a hierarchy of research evidence which assumes that some research designs are objectively better than others, and that choosing a "lesser" design is only acceptable when the better ones are not practically or ethically feasible [ 5 , 6 ]. Others, however, argue that an objective hierarchy does not exist, and that, instead, the research design and methods should be chosen to fit the specific research question at hand – "questions before methods" [ 2 , 7 – 9 ]. This means that even when an RCT is possible, some research problems require a different design that is better suited to addressing them. Arguing in JAMA, Berwick uses the example of rapid response teams in hospitals, which he describes as " a complex, multicomponent intervention – essentially a process of social change" susceptible to a range of different context factors including leadership or organisation history. According to him, "[in] such complex terrain, the RCT is an impoverished way to learn. Critics who use it as a truth standard in this context are incorrect" [ 8 ] . Instead of limiting oneself to RCTs, Berwick recommends embracing a wider range of methods , including qualitative ones, which for "these specific applications, (...) are not compromises in learning how to improve; they are superior" [ 8 ].

Research problems that can be approached particularly well using qualitative methods include assessing complex multi-component interventions or systems (of change), addressing questions beyond “what works”, towards “what works for whom when, how and why”, and focussing on intervention improvement rather than accreditation [ 7 , 9 – 12 ]. Using qualitative methods can also help shed light on the “softer” side of medical treatment. For example, while quantitative trials can measure the costs and benefits of neuro-oncological treatment in terms of survival rates or adverse effects, qualitative research can help provide a better understanding of patient or caregiver stress, visibility of illness or out-of-pocket expenses.

How to conduct qualitative research?

Given that qualitative research is characterised by flexibility, openness and responsivity to context, the steps of data collection and analysis are not as separate and consecutive as they tend to be in quantitative research [ 13 , 14 ]. As Fossey puts it : “sampling, data collection, analysis and interpretation are related to each other in a cyclical (iterative) manner, rather than following one after another in a stepwise approach” [ 15 ]. The researcher can make educated decisions with regard to the choice of method, how they are implemented, and to which and how many units they are applied [ 13 ]. As shown in Fig.  1 , this can involve several back-and-forth steps between data collection and analysis where new insights and experiences can lead to adaption and expansion of the original plan. Some insights may also necessitate a revision of the research question and/or the research design as a whole. The process ends when saturation is achieved, i.e. when no relevant new information can be found (see also below: sampling and saturation). For reasons of transparency, it is essential for all decisions as well as the underlying reasoning to be well-documented.

Iterative research process

While it is not always explicitly addressed, qualitative methods reflect a different underlying research paradigm than quantitative research (e.g. constructivism or interpretivism as opposed to positivism). The choice of methods can be based on the respective underlying substantive theory or theoretical framework used by the researcher [ 2 ].

Data collection

The methods of qualitative data collection most commonly used in health research are document study, observations, semi-structured interviews and focus groups [ 1 , 14 , 16 , 17 ].

Document study

Document study (also called document analysis) refers to the review by the researcher of written materials [ 14 ]. These can include personal and non-personal documents such as archives, annual reports, guidelines, policy documents, diaries or letters.

Observations

Observations are particularly useful to gain insights into a certain setting and actual behaviour – as opposed to reported behaviour or opinions [ 13 ]. Qualitative observations can be either participant or non-participant in nature. In participant observations, the observer is part of the observed setting, for example a nurse working in an intensive care unit [ 18 ]. In non-participant observations, the observer is “on the outside looking in”, i.e. present in but not part of the situation, trying not to influence the setting by their presence. Observations can be planned (e.g. for 3 h during the day or night shift) or ad hoc (e.g. as soon as a stroke patient arrives at the emergency room). During the observation, the observer takes notes on everything or certain pre-determined parts of what is happening around them, for example focusing on physician-patient interactions or communication between different professional groups. Written notes can be taken during or after the observations, depending on feasibility (which is usually lower during participant observations) and acceptability (e.g. when the observer is perceived to be judging the observed). Afterwards, these field notes are transcribed into observation protocols. If more than one observer was involved, field notes are taken independently, but notes can be consolidated into one protocol after discussions. Advantages of conducting observations include minimising the distance between the researcher and the researched, the potential discovery of topics that the researcher did not realise were relevant and gaining deeper insights into the real-world dimensions of the research problem at hand [ 18 ].

Semi-structured interviews

Hijmans & Kuyper describe qualitative interviews as “an exchange with an informal character, a conversation with a goal” [ 19 ]. Interviews are used to gain insights into a person’s subjective experiences, opinions and motivations – as opposed to facts or behaviours [ 13 ]. Interviews can be distinguished by the degree to which they are structured (i.e. a questionnaire), open (e.g. free conversation or autobiographical interviews) or semi-structured [ 2 , 13 ]. Semi-structured interviews are characterized by open-ended questions and the use of an interview guide (or topic guide/list) in which the broad areas of interest, sometimes including sub-questions, are defined [ 19 ]. The pre-defined topics in the interview guide can be derived from the literature, previous research or a preliminary method of data collection, e.g. document study or observations. The topic list is usually adapted and improved at the start of the data collection process as the interviewer learns more about the field [ 20 ]. Across interviews the focus on the different (blocks of) questions may differ and some questions may be skipped altogether (e.g. if the interviewee is not able or willing to answer the questions or for concerns about the total length of the interview) [ 20 ]. Qualitative interviews are usually not conducted in written format as it impedes on the interactive component of the method [ 20 ]. In comparison to written surveys, qualitative interviews have the advantage of being interactive and allowing for unexpected topics to emerge and to be taken up by the researcher. This can also help overcome a provider or researcher-centred bias often found in written surveys, which by nature, can only measure what is already known or expected to be of relevance to the researcher. Interviews can be audio- or video-taped; but sometimes it is only feasible or acceptable for the interviewer to take written notes [ 14 , 16 , 20 ].

Focus groups

Focus groups are group interviews to explore participants’ expertise and experiences, including explorations of how and why people behave in certain ways [ 1 ]. Focus groups usually consist of 6–8 people and are led by an experienced moderator following a topic guide or “script” [ 21 ]. They can involve an observer who takes note of the non-verbal aspects of the situation, possibly using an observation guide [ 21 ]. Depending on researchers’ and participants’ preferences, the discussions can be audio- or video-taped and transcribed afterwards [ 21 ]. Focus groups are useful for bringing together homogeneous (to a lesser extent heterogeneous) groups of participants with relevant expertise and experience on a given topic on which they can share detailed information [ 21 ]. Focus groups are a relatively easy, fast and inexpensive method to gain access to information on interactions in a given group, i.e. “the sharing and comparing” among participants [ 21 ]. Disadvantages include less control over the process and a lesser extent to which each individual may participate. Moreover, focus group moderators need experience, as do those tasked with the analysis of the resulting data. Focus groups can be less appropriate for discussing sensitive topics that participants might be reluctant to disclose in a group setting [ 13 ]. Moreover, attention must be paid to the emergence of “groupthink” as well as possible power dynamics within the group, e.g. when patients are awed or intimidated by health professionals.

Choosing the “right” method

As explained above, the school of thought underlying qualitative research assumes no objective hierarchy of evidence and methods. This means that each choice of single or combined methods has to be based on the research question that needs to be answered and a critical assessment with regard to whether or to what extent the chosen method can accomplish this – i.e. the “fit” between question and method [ 14 ]. It is necessary for these decisions to be documented when they are being made, and to be critically discussed when reporting methods and results.

Let us assume that our research aim is to examine the (clinical) processes around acute endovascular treatment (EVT), from the patient’s arrival at the emergency room to recanalization, with the aim to identify possible causes for delay and/or other causes for sub-optimal treatment outcome. As a first step, we could conduct a document study of the relevant standard operating procedures (SOPs) for this phase of care – are they up-to-date and in line with current guidelines? Do they contain any mistakes, irregularities or uncertainties that could cause delays or other problems? Regardless of the answers to these questions, the results have to be interpreted based on what they are: a written outline of what care processes in this hospital should look like. If we want to know what they actually look like in practice, we can conduct observations of the processes described in the SOPs. These results can (and should) be analysed in themselves, but also in comparison to the results of the document analysis, especially as regards relevant discrepancies. Do the SOPs outline specific tests for which no equipment can be observed or tasks to be performed by specialized nurses who are not present during the observation? It might also be possible that the written SOP is outdated, but the actual care provided is in line with current best practice. In order to find out why these discrepancies exist, it can be useful to conduct interviews. Are the physicians simply not aware of the SOPs (because their existence is limited to the hospital’s intranet) or do they actively disagree with them or does the infrastructure make it impossible to provide the care as described? Another rationale for adding interviews is that some situations (or all of their possible variations for different patient groups or the day, night or weekend shift) cannot practically or ethically be observed. In this case, it is possible to ask those involved to report on their actions – being aware that this is not the same as the actual observation. A senior physician’s or hospital manager’s description of certain situations might differ from a nurse’s or junior physician’s one, maybe because they intentionally misrepresent facts or maybe because different aspects of the process are visible or important to them. In some cases, it can also be relevant to consider to whom the interviewee is disclosing this information – someone they trust, someone they are otherwise not connected to, or someone they suspect or are aware of being in a potentially “dangerous” power relationship to them. Lastly, a focus group could be conducted with representatives of the relevant professional groups to explore how and why exactly they provide care around EVT. The discussion might reveal discrepancies (between SOPs and actual care or between different physicians) and motivations to the researchers as well as to the focus group members that they might not have been aware of themselves. For the focus group to deliver relevant information, attention has to be paid to its composition and conduct, for example, to make sure that all participants feel safe to disclose sensitive or potentially problematic information or that the discussion is not dominated by (senior) physicians only. The resulting combination of data collection methods is shown in Fig.  2 .

Possible combination of data collection methods

Attributions for icons: “Book” by Serhii Smirnov, “Interview” by Adrien Coquet, FR, “Magnifying Glass” by anggun, ID, “Business communication” by Vectors Market; all from the Noun Project

The combination of multiple data source as described for this example can be referred to as “triangulation”, in which multiple measurements are carried out from different angles to achieve a more comprehensive understanding of the phenomenon under study [ 22 , 23 ].

Data analysis

To analyse the data collected through observations, interviews and focus groups these need to be transcribed into protocols and transcripts (see Fig.  3 ). Interviews and focus groups can be transcribed verbatim , with or without annotations for behaviour (e.g. laughing, crying, pausing) and with or without phonetic transcription of dialects and filler words, depending on what is expected or known to be relevant for the analysis. In the next step, the protocols and transcripts are coded , that is, marked (or tagged, labelled) with one or more short descriptors of the content of a sentence or paragraph [ 2 , 15 , 23 ]. Jansen describes coding as “connecting the raw data with “theoretical” terms” [ 20 ]. In a more practical sense, coding makes raw data sortable. This makes it possible to extract and examine all segments describing, say, a tele-neurology consultation from multiple data sources (e.g. SOPs, emergency room observations, staff and patient interview). In a process of synthesis and abstraction, the codes are then grouped, summarised and/or categorised [ 15 , 20 ]. The end product of the coding or analysis process is a descriptive theory of the behavioural pattern under investigation [ 20 ]. The coding process is performed using qualitative data management software, the most common ones being InVivo, MaxQDA and Atlas.ti. It should be noted that these are data management tools which support the analysis performed by the researcher(s) [ 14 ].

From data collection to data analysis

Attributions for icons: see Fig. ​ Fig.2, 2 , also “Speech to text” by Trevor Dsouza, “Field Notes” by Mike O’Brien, US, “Voice Record” by ProSymbols, US, “Inspection” by Made, AU, and “Cloud” by Graphic Tigers; all from the Noun Project

How to report qualitative research?

Protocols of qualitative research can be published separately and in advance of the study results. However, the aim is not the same as in RCT protocols, i.e. to pre-define and set in stone the research questions and primary or secondary endpoints. Rather, it is a way to describe the research methods in detail, which might not be possible in the results paper given journals’ word limits. Qualitative research papers are usually longer than their quantitative counterparts to allow for deep understanding and so-called “thick description”. In the methods section, the focus is on transparency of the methods used, including why, how and by whom they were implemented in the specific study setting, so as to enable a discussion of whether and how this may have influenced data collection, analysis and interpretation. The results section usually starts with a paragraph outlining the main findings, followed by more detailed descriptions of, for example, the commonalities, discrepancies or exceptions per category [ 20 ]. Here it is important to support main findings by relevant quotations, which may add information, context, emphasis or real-life examples [ 20 , 23 ]. It is subject to debate in the field whether it is relevant to state the exact number or percentage of respondents supporting a certain statement (e.g. “Five interviewees expressed negative feelings towards XYZ”) [ 21 ].

How to combine qualitative with quantitative research?

Qualitative methods can be combined with other methods in multi- or mixed methods designs, which “[employ] two or more different methods [ …] within the same study or research program rather than confining the research to one single method” [ 24 ]. Reasons for combining methods can be diverse, including triangulation for corroboration of findings, complementarity for illustration and clarification of results, expansion to extend the breadth and range of the study, explanation of (unexpected) results generated with one method with the help of another, or offsetting the weakness of one method with the strength of another [ 1 , 17 , 24 – 26 ]. The resulting designs can be classified according to when, why and how the different quantitative and/or qualitative data strands are combined. The three most common types of mixed method designs are the convergent parallel design , the explanatory sequential design and the exploratory sequential design. The designs with examples are shown in Fig.  4 .

Three common mixed methods designs

In the convergent parallel design, a qualitative study is conducted in parallel to and independently of a quantitative study, and the results of both studies are compared and combined at the stage of interpretation of results. Using the above example of EVT provision, this could entail setting up a quantitative EVT registry to measure process times and patient outcomes in parallel to conducting the qualitative research outlined above, and then comparing results. Amongst other things, this would make it possible to assess whether interview respondents’ subjective impressions of patients receiving good care match modified Rankin Scores at follow-up, or whether observed delays in care provision are exceptions or the rule when compared to door-to-needle times as documented in the registry. In the explanatory sequential design, a quantitative study is carried out first, followed by a qualitative study to help explain the results from the quantitative study. This would be an appropriate design if the registry alone had revealed relevant delays in door-to-needle times and the qualitative study would be used to understand where and why these occurred, and how they could be improved. In the exploratory design, the qualitative study is carried out first and its results help informing and building the quantitative study in the next step [ 26 ]. If the qualitative study around EVT provision had shown a high level of dissatisfaction among the staff members involved, a quantitative questionnaire investigating staff satisfaction could be set up in the next step, informed by the qualitative study on which topics dissatisfaction had been expressed. Amongst other things, the questionnaire design would make it possible to widen the reach of the research to more respondents from different (types of) hospitals, regions, countries or settings, and to conduct sub-group analyses for different professional groups.

How to assess qualitative research?

A variety of assessment criteria and lists have been developed for qualitative research, ranging in their focus and comprehensiveness [ 14 , 17 , 27 ]. However, none of these has been elevated to the “gold standard” in the field. In the following, we therefore focus on a set of commonly used assessment criteria that, from a practical standpoint, a researcher can look for when assessing a qualitative research report or paper.

Assessors should check the authors’ use of and adherence to the relevant reporting checklists (e.g. Standards for Reporting Qualitative Research (SRQR)) to make sure all items that are relevant for this type of research are addressed [ 23 , 28 ]. Discussions of quantitative measures in addition to or instead of these qualitative measures can be a sign of lower quality of the research (paper). Providing and adhering to a checklist for qualitative research contributes to an important quality criterion for qualitative research, namely transparency [ 15 , 17 , 23 ].

Reflexivity

While methodological transparency and complete reporting is relevant for all types of research, some additional criteria must be taken into account for qualitative research. This includes what is called reflexivity, i.e. sensitivity to the relationship between the researcher and the researched, including how contact was established and maintained, or the background and experience of the researcher(s) involved in data collection and analysis. Depending on the research question and population to be researched this can be limited to professional experience, but it may also include gender, age or ethnicity [ 17 , 27 ]. These details are relevant because in qualitative research, as opposed to quantitative research, the researcher as a person cannot be isolated from the research process [ 23 ]. It may influence the conversation when an interviewed patient speaks to an interviewer who is a physician, or when an interviewee is asked to discuss a gynaecological procedure with a male interviewer, and therefore the reader must be made aware of these details [ 19 ].

Sampling and saturation

The aim of qualitative sampling is for all variants of the objects of observation that are deemed relevant for the study to be present in the sample “ to see the issue and its meanings from as many angles as possible” [ 1 , 16 , 19 , 20 , 27 ] , and to ensure “information-richness [ 15 ]. An iterative sampling approach is advised, in which data collection (e.g. five interviews) is followed by data analysis, followed by more data collection to find variants that are lacking in the current sample. This process continues until no new (relevant) information can be found and further sampling becomes redundant – which is called saturation [ 1 , 15 ] . In other words: qualitative data collection finds its end point not a priori , but when the research team determines that saturation has been reached [ 29 , 30 ].

This is also the reason why most qualitative studies use deliberate instead of random sampling strategies. This is generally referred to as “ purposive sampling” , in which researchers pre-define which types of participants or cases they need to include so as to cover all variations that are expected to be of relevance, based on the literature, previous experience or theory (i.e. theoretical sampling) [ 14 , 20 ]. Other types of purposive sampling include (but are not limited to) maximum variation sampling, critical case sampling or extreme or deviant case sampling [ 2 ]. In the above EVT example, a purposive sample could include all relevant professional groups and/or all relevant stakeholders (patients, relatives) and/or all relevant times of observation (day, night and weekend shift).

Assessors of qualitative research should check whether the considerations underlying the sampling strategy were sound and whether or how researchers tried to adapt and improve their strategies in stepwise or cyclical approaches between data collection and analysis to achieve saturation [ 14 ].

Good qualitative research is iterative in nature, i.e. it goes back and forth between data collection and analysis, revising and improving the approach where necessary. One example of this are pilot interviews, where different aspects of the interview (especially the interview guide, but also, for example, the site of the interview or whether the interview can be audio-recorded) are tested with a small number of respondents, evaluated and revised [ 19 ]. In doing so, the interviewer learns which wording or types of questions work best, or which is the best length of an interview with patients who have trouble concentrating for an extended time. Of course, the same reasoning applies to observations or focus groups which can also be piloted.

Ideally, coding should be performed by at least two researchers, especially at the beginning of the coding process when a common approach must be defined, including the establishment of a useful coding list (or tree), and when a common meaning of individual codes must be established [ 23 ]. An initial sub-set or all transcripts can be coded independently by the coders and then compared and consolidated after regular discussions in the research team. This is to make sure that codes are applied consistently to the research data.

Member checking

Member checking, also called respondent validation , refers to the practice of checking back with study respondents to see if the research is in line with their views [ 14 , 27 ]. This can happen after data collection or analysis or when first results are available [ 23 ]. For example, interviewees can be provided with (summaries of) their transcripts and asked whether they believe this to be a complete representation of their views or whether they would like to clarify or elaborate on their responses [ 17 ]. Respondents’ feedback on these issues then becomes part of the data collection and analysis [ 27 ].

Stakeholder involvement

In those niches where qualitative approaches have been able to evolve and grow, a new trend has seen the inclusion of patients and their representatives not only as study participants (i.e. “members”, see above) but as consultants to and active participants in the broader research process [ 31 – 33 ]. The underlying assumption is that patients and other stakeholders hold unique perspectives and experiences that add value beyond their own single story, making the research more relevant and beneficial to researchers, study participants and (future) patients alike [ 34 , 35 ]. Using the example of patients on or nearing dialysis, a recent scoping review found that 80% of clinical research did not address the top 10 research priorities identified by patients and caregivers [ 32 , 36 ]. In this sense, the involvement of the relevant stakeholders, especially patients and relatives, is increasingly being seen as a quality indicator in and of itself.

How not to assess qualitative research

The above overview does not include certain items that are routine in assessments of quantitative research. What follows is a non-exhaustive, non-representative, experience-based list of the quantitative criteria often applied to the assessment of qualitative research, as well as an explanation of the limited usefulness of these endeavours.

Protocol adherence

Given the openness and flexibility of qualitative research, it should not be assessed by how well it adheres to pre-determined and fixed strategies – in other words: its rigidity. Instead, the assessor should look for signs of adaptation and refinement based on lessons learned from earlier steps in the research process.

Sample size

For the reasons explained above, qualitative research does not require specific sample sizes, nor does it require that the sample size be determined a priori [ 1 , 14 , 27 , 37 – 39 ]. Sample size can only be a useful quality indicator when related to the research purpose, the chosen methodology and the composition of the sample, i.e. who was included and why.

Randomisation

While some authors argue that randomisation can be used in qualitative research, this is not commonly the case, as neither its feasibility nor its necessity or usefulness has been convincingly established for qualitative research [ 13 , 27 ]. Relevant disadvantages include the negative impact of a too large sample size as well as the possibility (or probability) of selecting “ quiet, uncooperative or inarticulate individuals ” [ 17 ]. Qualitative studies do not use control groups, either.

Interrater reliability, variability and other “objectivity checks”

The concept of “interrater reliability” is sometimes used in qualitative research to assess to which extent the coding approach overlaps between the two co-coders. However, it is not clear what this measure tells us about the quality of the analysis [ 23 ]. This means that these scores can be included in qualitative research reports, preferably with some additional information on what the score means for the analysis, but it is not a requirement. Relatedly, it is not relevant for the quality or “objectivity” of qualitative research to separate those who recruited the study participants and collected and analysed the data. Experiences even show that it might be better to have the same person or team perform all of these tasks [ 20 ]. First, when researchers introduce themselves during recruitment this can enhance trust when the interview takes place days or weeks later with the same researcher. Second, when the audio-recording is transcribed for analysis, the researcher conducting the interviews will usually remember the interviewee and the specific interview situation during data analysis. This might be helpful in providing additional context information for interpretation of data, e.g. on whether something might have been meant as a joke [ 18 ].

Not being quantitative research

Being qualitative research instead of quantitative research should not be used as an assessment criterion if it is used irrespectively of the research problem at hand. Similarly, qualitative research should not be required to be combined with quantitative research per se – unless mixed methods research is judged as inherently better than single-method research. In this case, the same criterion should be applied for quantitative studies without a qualitative component.

The main take-away points of this paper are summarised in Table ​ Table1. 1 . We aimed to show that, if conducted well, qualitative research can answer specific research questions that cannot to be adequately answered using (only) quantitative designs. Seeing qualitative and quantitative methods as equal will help us become more aware and critical of the “fit” between the research problem and our chosen methods: I can conduct an RCT to determine the reasons for transportation delays of acute stroke patients – but should I? It also provides us with a greater range of tools to tackle a greater range of research problems more appropriately and successfully, filling in the blind spots on one half of the methodological spectrum to better address the whole complexity of neurological research and practice.

Take-away-points

Acknowledgements

Abbreviations, authors’ contributions.

LB drafted the manuscript; WW and CG revised the manuscript; all authors approved the final versions.

no external funding.

Availability of data and materials

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

What is a Qualitative Survey? Meaning and Examples

Learn the definition of qualitative survey and examples of this research.

Whether your business is preparing to launch a new product or you’re taking steps to improve your company’s overall customer experience, collecting and interpreting qualitative data can be a necessary yet challenging endeavor. Businesses often rely on an in-depth qualitative survey to collect information that describes a consumer’s characteristics, patterns, and qualities. This data is then used to back up business decisions, helping brands recognize patterns and understand where they need to make changes and improvements.

Unlike quantitative research, which involves numbers and ratings that are easier to analyze, qualitative research is more nuanced. Instead of numbers that you can take at face value, qualitative data is more of a narrative that requires the researcher to make connections and inferences. So, how do businesses collect and analyze qualitative data? Here’s an introduction to qualitative survey methods , as well as some example questions to help you conduct this research on your own.

What is qualitative survey research?

Qualitative surveys are used to cultivate data that illustrates how people experience the world or, in the business world, how consumers experience products, services, and brands. Companies use qualitative surveys to explain or understand consumers’ behavior, characteristics, and motivations of people in a target group. The qualitative data collected can be used to inform businesses about what their audience thinks about new ideas for products or services. This content-rich data provides key insights into the feelings and meaning behind the behavior of your target audience.

In short, the goal of a qualitative survey is to uncover what people think and why they think that way. It’s based on a variety of social science disciplines, including psychology, sociology, and even anthropology.

Qualitative surveys and the research they support create opportunities for in-depth questioning of respondents based on their responses, as the interviewer tries to understand the subject’s feelings and motivations. For businesses, this data is invaluable—it helps you understand how your target audience makes decisions, so you can get to know your customers on their level.

There are several unique examples of qualitative research methods, including direct observation, case studies, ethnographic research, and more. When businesses conduct qualitative research, though, they typically do so using two main modes of data collection: interviews and surveys.

One of the best ways to collect high-quality qualitative data is through a direct interview. A one-on-one interview—whether in person, over the phone, or over a video call—is a personal, conversational method that helps the interviewer garner in-depth details from the respondent.

Focus groups are another common type of interview. They usually include a limited number of respondents, and an advantage of this method is that the interviewer can hear customer feedback in their own words and voices, since the group setting often helps individual respondents feel more empowered. It’s a great way to discover ideas and issues that the interviewer may not have even considered but are still important to the group.

When it comes to direct interviews, the most important consideration is asking the right questions. Researchers should come to the interview prepared with follow-up questions to get the most valuable information from the respondent.

A qualitative survey is a helpful tool for researchers looking to get honest qualitative data from their target audience. A survey that asks the right questions is an excellent way to get insightful answers quickly.

While qualitative surveys don’t give researchers as much real-time feedback as an in-person interview would, they do give the interviewer more of a chance to encourage responses that are more elaborate and provide more perspective. It’s important to ask open-ended questions that encourage respondents to explain or describe their thoughts and feelings in great detail.

Since you can create a standardized survey and ask many of the same questions as you would in a one-on-one interview, a qualitative survey is often a faster way to cultivate high-quality qualitative data. Qualitative survey research is a great method if you want to enlarge your sample size and collect qualitative data at scale.

Examples of qualitative survey questions

Qualitative research requires both the researcher and respondents to go in-depth. By asking the right questions, a surveyor can cultivate responses that provide a clear picture of a customer’s attitudes, patterns, perceptions, and more.

Researchers should ask specific, as opposed to generic, questions with a clear purpose. As mentioned above, be prepared with some sub-questions, to encourage the respondent to provide an in-depth, meaningful answer.

Here are some examples of qualitative survey questions that can elicit useful responses:

• Why did you/will you buy this product?
• What is your overall perception of this product/brand?
• How does this product/brand make you feel?
• What sets this product/brand apart from its competitors?
• How does this product solve your particular needs?
• What needs do you have that this product/brand isn’t solving?

As for sub-questions, make sure to ask open-ended questions that can’t be answered with a simple “yes” or “no.” By paying close attention to your respondent’s initial response to each question, you can ask leading questions that help you narrow your focus. You might find that as you go through the survey process, you may need to refine your questions to get the type of in-depth responses you’re looking for.

Conduct a meaningful qualitative survey with Voiceform

A useful qualitative survey relies on high-quality data, and the way you collect that data matters. Some members of your target audience may be reluctant to share their thoughts and feelings in person or even through written responses, and that’s where Voiceform comes in.

Voiceform helps you collect data and customer feedback in a way that’s easy on both you and your customer. Using innovative solutions to gather and transcribe multimedia feedback, it’s easy to cultivate high-quality data that reflects true customer sentiment, so you can analyze and use it as you see fit. The platform even includes useful quantitative and qualitative analysis tools, making it easy for you to monitor public perception of your products or your brand as a whole.

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surveys | August 27, 2020

The Guide to Qualitative Research: Methods, Types, and Examples

Daniel Ndukwu

Qualitative research is an important part of any project. It gives you insights that quantitative research can’t hope to match.

To receive the benefits that qualitative research can bring to the table, it’s essential to do it properly. That’s easier said than done.

This in-depth guide will give you a better understanding of qualitative research, how it can be used, the methods for carrying it out, and its limitations.

Table of Contents

What is qualitative research?

Qualitative research is the process of gathering non-numerical data that helps you understand the deeper meaning behind a topic. It can help you decipher the motivations, thought processes, and opinions of people who are experiencing the problem or situation.

For example, an entrepreneur wants to start a shoe brand targeted at a younger demographic. They know younger people spend more money on name-brand basketball shoes. Qualitative research will help them understand the motivations and thought processes behind why those shoes are appealing.

With the help of capable marketing teams and mentors , they can use this data to craft communication plans that will resonate with their audience.

The data gained helps develop better hypotheses, confirm or disprove theories, and informs quantitative research studies. There are multiple quantitative research methods that are ideal for certain situations and this guide delves deeper into those data collection processes .

Keep in mind that qualitative research gives you descriptive data that must then be analyzed and interpreted. This process is much more difficult than a quantitative analysis which is why many organizations opt to skip it entirely.

What’s the purpose of qualitative research?

Qualitative research was popularized by psychologists and sociologists who were unhappy with the scientific method in use. Traditional scientific methods were only able to tell what was happening but failed to understand why.

Qualitative research, on the other hand, seeks to find the deeper meaning behind actions and situations. For example, you may realize a relationship between two things exist like poverty and lower literacy rates. It’s qualitative data that can help you understand why this relationship exists.

In the diverse landscape of qualitative research its application extends beyond conventional fields offering valuable insights in specialized areas take for instance the legal sector where understanding nuanced human experiences is crucial a cerebral palsy lawyer leveraging qualitative research delves deeper into the multifaceted experiences of individuals and families impacted by cerebral palsy this methodical approach aids in comprehending the broader social emotional and economic ramifications thereby guiding more compassionate and effective legal representation.

When should qualitative research be used

There’s a simple stress test to understand whether qualitative research or quantitative research should be used. Ask yourself the following questions:

• Do you have a clear understanding of the problem? If not, use it;
• Do you understand the reasons that contribute to the problem or situation? If not, use it;
• Are the attitudes of the people who experience or display the behavior clear to you? If not, use it;
• Have you already analyzed first-person accounts or research related to the topic? If not, use it.

Qualitative research vs quantitative research

There’s a big difference between the two types of research. For the most part, qualitative research is exploratory. You’re trying to figure out the reasons behind situations and form a clearer hypothesis. Those hypotheses are then tested with further qualitative or quantitative research.

Quantitative research focuses on collecting numerical data that can be used to quantify the magnitude of a situation. The data gained can be organized and statistical analysis carried out.

For example, qualitative research may tell you that people in lower-income areas drop out of school and have lower literacy rates. Quantitative research can tell you the percentage of people that end up dropping out of school within a given population.

As you can see, they work together to give you a holistic understanding of a market or problem.

Qualitative research data collection Methods

We’ve written an in-depth guide about the data collection methods you can use for both quantitative and qualitative research. This section will give you a quick overview of the data collection methods available.

The first data collection method and the most common are surveys. More specifically, surveys with open-ended questions . These give your respondents the opportunity to explain things with their own words.

Another benefit of surveys, especially with online survey tools like KyLeads is that you can quickly distribute your survey to a huge audience. This can cut down on your costs while still giving you the insights you need.

There are two problems with surveys. The first one is that you’re unable to ask relevant clarifying questions. Some of the data you collect may be unclear and lead you to the wrong conclusions.

The second problem is that respondents, unless adequately incentivized, may abandon the survey or give inadequate answers. This is known as survey fatigue and is a challenge when you have longer surveys. You can mitigate the effects by placing the most important questions first.

Focus groups

A focus group involves 3 – 10 people and a specialized moderator. Groups larger than ten should be broken up and those fewer than three won’t be able to deliver the insights you need.

The benefits of a focus group come from the ability to recreate specific situations or test scenarios before they happen. To get the most out of the focus group, it’s important to carefully select the participants based on their demographic and psychographic profiles .

The advantage of a focus group is that the information is insightful and comes from multiple people within your target market. The disadvantage is that groupthink can be a real problem.

You can prevent groupthink by having people write their opinions down before voicing them and even assigning one person to play devil’s advocate. Don’t discourage divergent opinions or perspectives.

Another challenge is that focus groups are expensive compared to other methods listed here. The participants are usually paid for their time and it requires things like meeting space and specialized staff.

Interviews are an old staple of qualitative research and are almost as common as surveys. Interviews can be conducted over the phone, in person, or even through a video conference. The important part is that they’re real-time and you can ask clarifying questions so you don’t draw the wrong conclusions.

There are multiple types of interviews. You can use structured interviews, unstructured interviews, or semi-structured interviews. Keep in mind that the structured interview may not be the best option if you’re doing exploratory =research.

Observation/immersion

This is the process of observing the ongoing behavior of an individual or group. It’s most prevalent in social sciences and marketing applications. This data collection method is the most passive and may not be ideal when doing initial exploratory research. You may be drawing conclusions on incomplete information.

There is an option of participating actively in what you’re observing. Keep in mind that this is frowned upon because the researcher may accidentally introduce biases. The biggest disadvantage is that some things simply can’t be observed by a researcher without interaction.

Try to use team collaboration to cut down on the biases that will be introduced. Compare notes and, as much as possible, look at things objectively. A teammate is invaluable for this kind of exercise.

Pros and cons of qualitative research

Qualitative research is powerful and has many benefits but it also has multiple disadvantages you should be aware of before jumping in.

• Get a deep understanding of the behaviors and attitudes of your target group
• You can get those insights from smaller samples sizes
• As long as you choose the right aspects to focus on and groups to work with, the insights can have much wider applications.
• Helps reduce biases because you’re doing exploratory research to get a baseline of information
• Most qualitative research is fluid meaning it adapts to the inputs to get a better understanding of the overall situation
• The data itself is subjective because it’s based on the experiences and biases of the respondents
• It’s more expensive than quantitative research
• It can take much longer to go through the more involved data collection methods like focus groups and interviews
• It’s more difficult to analyze and often requires people with specialized skills
• It’s nonnumerical in nature so statistical analysis cannot be applied to the data
• Results can’t be easily replicated following the scientific method

Qualitative research can be a powerful tool in your arsenal but there are many things to take into consideration. It tends to take longer to collect the data and analyze it. It’s also more expensive than most quantitative research methods.

Before diving into a qualitative research strategy, define clear goals, a timeframe for completion, and the kind of information you need to solve your problem.

Let me know what you think in the comments and don’t forget to share.

what types of questionnaire appropriate to be use in qualitative research ?

This guide will give you a detailed answer https://www.kyleads.com/blog/questionnaire/

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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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83 Qualitative Research Questions & Examples

Qualitative research questions help you understand consumer sentiment. They’re strategically designed to show organizations how and why people feel the way they do about a brand, product, or service. It looks beyond the numbers and is one of the most telling types of market research a company can do.

The UK Data Service describes this perfectly, saying, “The value of qualitative research is that it gives a voice to the lived experience .”

Read on to see seven use cases and 83 qualitative research questions, with the added bonus of examples that show how to get similar insights faster with Similarweb Digital Research Intelligence.

What is a qualitative research question?

A qualitative research question explores a topic in-depth, aiming to better understand the subject through interviews, observations, and other non-numerical data. Qualitative research questions are open-ended, helping to uncover a target audience’s opinions, beliefs, and motivations.

How to choose qualitative research questions?

Choosing the right qualitative research questions can be incremental to the success of your research and the findings you uncover. Here’s my six-step process for choosing the best qualitative research questions.

• Start by understanding the purpose of your research. What do you want to learn? What outcome are you hoping to achieve?
• Consider who you are researching. What are their experiences, attitudes, and beliefs? How can you best capture these in your research questions ?
• Keep your questions open-ended . Qualitative research questions should not be too narrow or too broad. Aim to ask specific questions to provide meaningful answers but broad enough to allow for exploration.
• Balance your research questions. You don’t want all of your questions to be the same type. Aim to mix up your questions to get a variety of answers.
• Ensure your research questions are ethical and free from bias. Always have a second (and third) person check for unconscious bias.
• Consider the language you use. Your questions should be written in a way that is clear and easy to understand. Avoid using jargon , acronyms, or overly technical language.

Types of qualitative research questions

For a question to be considered qualitative, it usually needs to be open-ended. However, as I’ll explain, there can sometimes be a slight cross-over between quantitative and qualitative research questions.

Open-ended questions

These allow for a wide range of responses and can be formatted with multiple-choice answers or a free-text box to collect additional details. The next two types of qualitative questions are considered open questions, but each has its own style and purpose.

• Probing questions are used to delve deeper into a respondent’s thoughts, such as “Can you tell me more about why you feel that way?”
• Comparative questions ask people to compare two or more items, such as “Which product do you prefer and why?” These qualitative questions are highly useful for understanding brand awareness , competitive analysis , and more.

Closed-ended questions

These ask respondents to choose from a predetermined set of responses, such as “On a scale of 1-5, how satisfied are you with the new product?” While they’re traditionally quantitative, adding a free text box that asks for extra comments into why a specific rating was chosen will provide qualitative insights alongside their respective quantitative research question responses.

• Ranking questions get people to rank items in order of preference, such as “Please rank these products in terms of quality.” They’re advantageous in many scenarios, like product development, competitive analysis, and brand awareness.
• Likert scale questions ask people to rate items on a scale, such as “On a scale of 1-5, how satisfied are you with the new product?” Ideal for placement on websites and emails to gather quick, snappy feedback.

Qualitative research question examples

There are many applications of qualitative research and lots of ways you can put your findings to work for the success of your business. Here’s a summary of the most common use cases for qualitative questions and examples to ask.

Qualitative questions for identifying customer needs and motivations

These types of questions help you find out why customers choose products or services and what they are looking for when making a purchase.

• What factors do you consider when deciding to buy a product?
• What would make you choose one product or service over another?
• What are the most important elements of a product that you would buy?
• What features do you look for when purchasing a product?
• What qualities do you look for in a company’s products?
• Do you prefer localized or global brands when making a purchase?
• How do you determine the value of a product?
• What do you think is the most important factor when choosing a product?
• How do you decide if a product or service is worth the money?
• Do you have any specific expectations when purchasing a product?
• Do you prefer to purchase products or services online or in person?
• What kind of customer service do you expect when buying a product?
• How do you decide when it is time to switch to a different product?
• Where do you research products before you decide to buy?
• What do you think is the most important customer value when making a purchase?

Qualitative research questions to enhance customer experience

Use these questions to reveal insights into how customers interact with a company’s products or services and how those experiences can be improved.

• What aspects of our product or service do customers find most valuable?
• How do customers perceive our customer service?
• What factors are most important to customers when purchasing?
• What do customers think of our brand?
• What do customers think of our current marketing efforts?
• How do customers feel about the features and benefits of our product?
• How do customers feel about the price of our product or service?
• How could we improve the customer experience?
• What do customers think of our website or app?
• What do customers think of our customer support?
• What could we do to make our product or service easier to use?
• What do customers think of our competitors?
• What is your preferred way to access our site?
• How do customers feel about our delivery/shipping times?
• What do customers think of our loyalty programs?

Qualitative research question example for customer experience

• 🙋‍♀️ Question: What is your preferred way to access our site?
• 🤓 Insight sought: How mobile-dominant are consumers? Should you invest more in mobile optimization or mobile marketing?
• 🤯 Challenges with traditional qualitative research methods: While using this type of question is ideal if you have a large database to survey when placed on a site or sent to a limited customer list, it only gives you a point-in-time perspective from a limited group of people.
• 💡 A new approach: You can get better, broader insights quicker with Similarweb Digital Research Intelligence. To fully inform your research, you need to know preferences at the industry or market level.
• ⏰ Time to insight: 30 seconds
• ✅ How it’s done: Similarweb offers multiple ways to answer this question without going through a lengthy qualitative research process. 

First, I’m going to do a website market analysis of the banking credit and lending market in the finance sector to get a clearer picture of industry benchmarks.

Here, I can view device preferences across any industry or market instantly. It shows me the device distribution for any country across any period. This clearly answers the question of how mobile dominate my target audience is , with 59.79% opting to access site via a desktop vs. 40.21% via mobile

I then use the trends section to show me the exact split between mobile and web traffic for each key player in my space. Let’s say I’m about to embark on a competitive campaign that targets customers of Chase and Bank of America ; I can see both their audiences are highly desktop dominant compared with others in their space .

Qualitative question examples for developing new products or services

Research questions like this can help you understand customer pain points and give you insights to develop products that meet those needs.

• What is the primary reason you would choose to purchase a product from our company?
• How do you currently use products or services that are similar to ours?
• Is there anything that could be improved with products currently on the market?
• What features would you like to see added to our products?
• How do you prefer to contact a customer service team?
• What do you think sets our company apart from our competitors?
• What other product or service offerings would like to see us offer?
• What type of information would help you make decisions about buying a product?
• What type of advertising methods are most effective in getting your attention?
• What is the biggest deterrent to purchasing products from us?

Qualitative research question example for service development

• 🙋‍♀️ Question: What type of advertising methods are most effective in getting your attention?
• 🤓 Insight sought: The marketing channels and/or content that performs best with a target audience .
• 🤯 Challenges with traditional qualitative research methods: When using qualitative research surveys to answer questions like this, the sample size is limited, and bias could be at play.
• 💡 A better approach: The most authentic insights come from viewing real actions and results that take place in the digital world. No questions or answers are needed to uncover this intel, and the information you seek is readily available in less than a minute.
• ⏰ Time to insight: 5 minutes
• ✅ How it’s done: There are a few ways to approach this. You can either take an industry-wide perspective or hone in on specific competitors to unpack their individual successes. Here, I’ll quickly show a snapshot with a whole market perspective.

Using the market analysis element of Similarweb Digital Research Intelligence, I select my industry or market, which I’ve kept as banking and credit. A quick click into marketing channels shows me which channels drive the highest traffic in my market. Taking direct traffic out of the equation, for now, I can see that referrals and organic traffic are the two highest-performing channels in this market.

Similarweb allows me to view the specific referral partners and pages across these channels. 

Looking closely at referrals in this market, I’ve chosen chase.com and its five closest rivals . I select referrals in the channel traffic element of marketing channels. I see that Capital One is a clear winner, gaining almost 25 million visits due to referral partnerships.

Next, I get to see exactly who is referring traffic to Capital One and the total traffic share for each referrer. I can see the growth as a percentage and how that has changed, along with an engagement score that rates the average engagement level of that audience segment. This is particularly useful when deciding on which new referral partnerships to pursue.  

Once I’ve identified the channels and campaigns that yield the best results, I can then use Similarweb to dive into the various ad creatives and content that have the greatest impact.

These ads are just a few of those listed in the creatives section from my competitive website analysis of Capital One. You can filter this list by the specific campaign, publishers, and ad networks to view those that matter to you most. You can also discover video ad creatives in the same place too.

In just five minutes ⏰ 

• I’ve captured audience loyalty statistics across my market
• Spotted the most competitive players
• Identified the marketing channels my audience is most responsive to
• I know which content and campaigns are driving the highest traffic volume
• I’ve created a target list for new referral partners and have been able to prioritize this based on results and engagement figures from my rivals
• I can see the types of creatives that my target audience is responding to, giving me ideas for ways to generate effective copy for future campaigns

Qualitative questions to determine pricing strategies

Companies need to make sure pricing stays relevant and competitive. Use these questions to determine customer perceptions on pricing and develop pricing strategies to maximize profits and reduce churn.

• How do you feel about our pricing structure?
• How does our pricing compare to other similar products?
• What value do you feel you get from our pricing?
• How could we make our pricing more attractive?
• What would be an ideal price for our product?
• Which features of our product that you would like to see priced differently?
• What discounts or deals would you like to see us offer?
• How do you feel about the amount you have to pay for our product?

Get Faster Answers to Qualitative Research Questions with Similarweb Today

Qualitative research question example for determining pricing strategies.

• 🙋‍♀️ Question: What discounts or deals would you like to see us offer?
• 🤓 Insight sought: The promotions or campaigns that resonate with your target audience.
• 🤯 Challenges with traditional qualitative research methods: Consumers don’t always recall the types of ads or campaigns they respond to. Over time, their needs and habits change. Your sample size is limited to those you ask, leaving a huge pool of unknowns at play.
• 💡 A better approach: While qualitative insights are good to know, you get the most accurate picture of the highest-performing promotion and campaigns by looking at data collected directly from the web. These analytics are real-world, real-time, and based on the collective actions of many, instead of the limited survey group you approach. By getting a complete picture across an entire market, your decisions are better informed and more aligned with current market trends and behaviors.
• ✅ How it’s done: Similarweb’s Popular Pages feature shows the content, products, campaigns, and pages with the highest growth for any website. So, if you’re trying to unpack the successes of others in your space and find out what content resonates with a target audience, there’s a far quicker way to get answers to these questions with Similarweb.

Here, I’m using Capital One as an example site. I can see trending pages on their site showing the largest increase in page views. Other filters include campaign, best-performing, and new–each of which shows you page URLs, share of traffic , and growth as a percentage. This page is particularly useful for staying on top of trending topics , campaigns, and new content being pushed out in a market by key competitors.

Qualitative research questions for product development teams

It’s vital to stay in touch with changing consumer needs. These questions can also be used for new product or service development, but this time, it’s from the perspective of a product manager or development team. 

• What are customers’ primary needs and wants for this product?
• What do customers think of our current product offerings?
• What is the most important feature or benefit of our product?
• How can we improve our product to meet customers’ needs better?
• What do customers like or dislike about our competitors’ products?
• What do customers look for when deciding between our product and a competitor’s?
• How have customer needs and wants for this product changed over time?
• What motivates customers to purchase this product?
• What is the most important thing customers want from this product?
• What features or benefits are most important when selecting a product?
• What do customers perceive to be our product’s pros and cons?
• What would make customers switch from a competitor’s product to ours?
• How do customers perceive our product in comparison to similar products?
• What do customers think of our pricing and value proposition?
• What do customers think of our product’s design, usability, and aesthetics?

Qualitative questions examples to understand customer segments

Market segmentation seeks to create groups of consumers with shared characteristics. Use these questions to learn more about different customer segments and how to target them with tailored messaging.

• What motivates customers to make a purchase?
• How do customers perceive our brand in comparison to our competitors?
• How do customers feel about our product quality?
• How do customers define quality in our products?
• What factors influence customers’ purchasing decisions ?
• What are the most important aspects of customer service?
• What do customers think of our customer service?
• What do customers think of our pricing?
• How do customers rate our product offerings?
• How do customers prefer to make purchases (online, in-store, etc.)?

Qualitative research question example for understanding customer segments

• 🙋‍♀️ Question: Which social media channels are you most active on?
• 🤓 Insight sought: Formulate a social media strategy . Specifically, the social media channels most likely to succeed with a target audience.
• 🤯 Challenges with traditional qualitative research methods: Qualitative research question responses are limited to those you ask, giving you a limited sample size. Questions like this are usually at risk of some bias, and this may not be reflective of real-world actions.
• 💡 A better approach: Get a complete picture of social media preferences for an entire market or specific audience belonging to rival firms. Insights are available in real-time, and are based on the actions of many, not a select group of participants. Data is readily available, easy to understand, and expandable at a moment’s notice.
• ✅ How it’s done: Using Similarweb’s website analysis feature, you can get a clear breakdown of social media stats for your audience using the marketing channels element. It shows the percentage of visits from each channel to your site, respective growth, and specific referral pages by each platform. All data is expandable, meaning you can select any platform, period, and region to drill down and get more accurate intel, instantly.

This example shows me Bank of America’s social media distribution, with YouTube , Linkedin , and Facebook taking the top three spots, and accounting for almost 80% of traffic being driven from social media.

When doing any type of market research, it’s important to benchmark performance against industry averages and perform a social media competitive analysis to verify rival performance across the same channels.

Qualitative questions to inform competitive analysis

Organizations must assess market sentiment toward other players to compete and beat rival firms. Whether you want to increase market share , challenge industry leaders , or reduce churn, understanding how people view you vs. the competition is key.

• What is the overall perception of our competitors’ product offerings in the market?
• What attributes do our competitors prioritize in their customer experience?
• What strategies do our competitors use to differentiate their products from ours?
• How do our competitors position their products in relation to ours?
• How do our competitors’ pricing models compare to ours?
• What do consumers think of our competitors’ product quality?
• What do consumers think of our competitors’ customer service?
• What are the key drivers of purchase decisions in our market?
• What is the impact of our competitors’ marketing campaigns on our market share ? 10. How do our competitors leverage social media to promote their products?

Qualitative research question example for competitive analysis

• 🙋‍♀️ Question: What other companies do you shop with for x?
• 🤓 Insight sought: W ho are your competitors? Which of your rival’s sites do your customers visit? How loyal are consumers in your market?
• 🤯 Challenges with traditional qualitative research methods:  Sample size is limited, and customers could be unwilling to reveal which competitors they shop with, or how often they around. Where finances are involved, people can act with reluctance or bias, and be unwilling to reveal other suppliers they do business with.
• 💡 A better approach: Get a complete picture of your audience’s loyalty, see who else they shop with, and how many other sites they visit in your competitive group. Find out the size of the untapped opportunity and which players are doing a better job at attracting unique visitors – without having to ask people to reveal their preferences.
• ✅ How it’s done: Similarweb website analysis shows you the competitive sites your audience visits, giving you access to data that shows cross-visitation habits, audience loyalty, and untapped potential in a matter of minutes.

Using the audience interests element of Similarweb website analysis, you can view the cross-browsing behaviors of a website’s audience instantly. You can see a matrix that shows the percentage of visitors on a target site and any rival site they may have visited.

With the Similarweb audience overlap feature, view the cross-visitation habits of an audience across specific websites. In this example, I chose chase.com and its four closest competitors to review. For each intersection, you see the number of unique visitors and the overall proportion of each site’s audience it represents. It also shows the volume of unreached potential visitors.

Here, you can see a direct comparison of the audience loyalty represented in a bar graph. It shows a breakdown of each site’s audience based on how many other sites they have visited. Those sites with the highest loyalty show fewer additional sites visited.

From the perspective of chase.com, I can see 47% of their visitors do not visit rival sites. 33% of their audience visited 1 or more sites in this group, 14% visited 2 or more sites, 4% visited 3 or more sites, and just 0.8% viewed all sites in this comparison. 

How to answer qualitative research questions with Similarweb

Similarweb Digital Research Intelligence drastically improves market research efficiency and time to insight. Both of these can impact the bottom line and the pace at which organizations can adapt and flex when markets shift, and rivals change tactics.

Outdated practices, while still useful, take time . And with a quicker, more efficient way to garner similar insights, opting for the fast lane puts you at a competitive advantage.

With a birds-eye view of the actions and behaviors of companies and consumers across a market , you can answer certain research questions without the need to plan, do, and review extensive qualitative market research .

Wrapping up

Qualitative research methods have been around for centuries. From designing the questions to finding the best distribution channels, collecting and analyzing findings takes time to get the insights you need. Similarweb Digital Research Intelligence drastically improves efficiency and time to insight. Both of which impact the bottom line and the pace at which organizations can adapt and flex when markets shift.

Similarweb’s suite of digital intelligence solutions offers unbiased, accurate, honest insights you can trust for analyzing any industry, market, or audience.

• Methodologies used for data collection are robust, transparent, and trustworthy.
• Clear presentation of data via an easy-to-use, intuitive platform.
• It updates dynamically–giving you the freshest data about an industry or market.
• Data is available via an API – so you can plug into platforms like Tableau or PowerBI to streamline your analyses.
• Filter and refine results according to your needs.

Are quantitative or qualitative research questions best?

Both have their place and purpose in market research. Qualitative research questions seek to provide details, whereas quantitative market research gives you numerical statistics that are easier and quicker to analyze. You get more flexibility with qualitative questions, and they’re non-directional.

What are the advantages of qualitative research?

Qualitative research is advantageous because it allows researchers to better understand their subject matter by exploring people’s attitudes, behaviors, and motivations in a particular context. It also allows researchers to uncover new insights that may not have been discovered with quantitative research methods.

What are some of the challenges of qualitative research?

Qualitative research can be time-consuming and costly, typically involving in-depth interviews and focus groups. Additionally, there are challenges associated with the reliability and validity of the collected data, as there is no universal standard for interpreting the results.

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Qualitative Research Methods: Types, Examples, and Analysis

In a universe swarming with data, numbers, and algorithms, lies a lesser-known realm where emotions, stories, and intimate revelations take center stage. When you want to get inside your customers’ heads to understand their thoughts, feelings, perceptions, beliefs, and emotions, numbers are unlikely to provide a complete picture.

Let’s set the scene: picture a cozy bakery buzzing with conversations. People from different walks of life gather, each carrying a unique story to tell. You observe that your sale of pancakes is more than that of pastries, numerical data will tell you that much. But numbers won’t tell you why.

This is exactly where qualitative surveys come into play; they take you right to the heart of people’s minds and experiences – the “why” behind the statistics.

Quantitative data may offer a bird’s-eye view of the crowd, but qualitative surveys open the doorways to your audience’s individual tales. In this blog, we are going to explore qualitative research, its types, analytical procedures, positive and negative aspects, and examples.

Here we go!

What Is Qualitative Research?

Qualitative research is a branch of market research that involves collecting and analyzing qualitative data through open-ended communication. The primary purpose of conducting qualitative research is to understand the individual’s thoughts, feelings, opinions, and reasons behind these emotions.

It is used to gather in-depth and rich insights into a particular topic. Understanding how your audience feels about a specific subject helps make informed decisions in research.

As opposed to quantitative research, qualitative research does not deal with the collection of numerical data for statistical analysis. The application of this research method is usually found in humanities and social science subjects like sociology, history, anthropology, health science, education, etc.

Types of Qualitative Research Methods

Qualitative research methods are designed to understand the behavior and perception of the target audience about a particular subject.

Qualitative research methods include observations, one-on-one interviews, case study research, focus groups, ethnographic research, phenomenology, and grounded theory.

Let’s discuss them one by one.

1. Observations

Observation is one of the oldest qualitative methods of research used to collect systematic data using subjective methodologies. It is based on five primary sense organs – smell, sight, taste, touch, and hearing, and their functioning. This method focuses on characteristics and qualities rather than numbers.

The qualitative observation technique involves observing the interaction patterns in a particular situation. Researchers collect data by closely watching the behaviors of others. They rely on their ability to observe the target audience rather than communicating with people about their thoughts on a particular subject.

2. One-on-One Interviews

Conducting one-on-one interviews is one of the most common types of qualitative research methods. Although both open-ended and closed-ended questions can be a part of these interviews, open-ended conservation between researchers and participants related to a particular subject is still the preferred mode of communication. This is to gather in-depth qualitative data for the research purpose.

Here, the researcher asks pre-determined questions to the participants to collect specific information about their research topic. Interviews can be conducted face-to-face, by email, or by phone. The drawback of this method is that sometimes the participants feel uncomfortable sharing honest answers with the researcher.

3. Focus Groups

A Focus group involves collecting qualitative data by conducting a group discussion of 6-12 members along with a moderator related to a particular subject. Here the moderator asks respondents a set of predetermined questions so that they can interact with each other and form a group discussion. It helps researchers to collect rich qualitative data about their market research.

However, it is essential to ensure that the moderator asks open-ended questions like “how,” “what,” and “why” that will enable participants to share their thoughts and feelings.

Close-ended questions like “yes” and “no” should be avoided as they do not lead to engagement among participants.

4. Case Study Research

A case study is another example of qualitative research that involves a comprehensive examination of a particular subject, person, or event.

This method is used to obtain in-depth data and complete knowledge of the subject. The data is collected from various sources like interviews and observation to supplement the conclusion.

This qualitative approach is extensively used in the field of social sciences, law, business, and health. Many companies use this technique when marketing their products/services to new customers. It tells them how their business offerings can solve a particular problem. Let’s discuss an example of this method of qualitative research.

5. Digital Ethnography

This is an innovative form of qualitative research that focuses on understanding people and their cultures in the context of the digital realm. Digital ethnography aims to study individuals’ behavior, interactions, and social dynamics within online environments and digital communities.

In digital ethnography, the researcher acts as both an observer and a participant in these said online communities to gain firsthand insight into the lifestyles, cultures, and traditions of people navigating these digital landscapes.

Unlike traditional ethnography, digital ethnography is more efficient and accessible. The studies are conducted remotely, reducing the need for extended physical presence in a specific location, and the data collection process is often more streamlined.

6. Grounded Theory

This is another data collection method of qualitative research used across various disciplines. The Grounded Theory aims to provide the reasons, theories, and explanations behind an event. It focuses on why a course of action has happened the way it did.

The grounded theory model collects and analyzes the data to develop new theories about the subject. The data is collected using different techniques like observation, literature review, and document analysis.

This qualitative method is majorly used in business for conducting user satisfaction surveys to explain why a customer purchases a particular product or service. It helps companies in managing customer loyalty.

Watch: How to Create a Customer Satisfaction Survey

7. Phenomenology

Phenomenology is another qualitative research example that describes how an individual experiences or feels about a particular event. It also explores the experience of a specific event in a community.

Here, the researcher interviews people who have experienced a particular event to find similarities between their experiences. The researcher can also record what they learn from the target audience to maintain the credibility of the data.

Although this qualitative technique depends majorly on interviews, other data collection methods like observation, interviews, and survey questionnaires are also used to supplement the findings. The application of this method is found in psychology, philosophy, and education.

For example, to prompt a participant to share their experience around an event they encountered, you can ask:

“What was your experience like when you first encountered [a specific phenomenon or event]?”

8. Record Keeping

This approach involves using existing trustworthy documents and other reliable sources as the basis of data for new research. It’s comparable to visiting a library, where you can explore books and reference materials to gather relevant data that might be helpful for your research.

How Do You Analyze Qualitative Data?

1. Arranging the Data

Qualitative data is collected in different forms like audio recordings, interviews, video transcriptions, etc. This step involves arranging all the collected data in the text format in the spreadsheet. This can be done either manually or with the help of data analysis tools.

2. Organizing the Data

Even after putting the data into a spreadsheet, the data is still messy and hard to read. Due to this, the data needs to be organized in a readable and understandable pattern.

For example, you can organize data based on questions asked. Organize your data in such a way that it appears visually clear. Data organization can be tedious, but it is essential for the next step.

3. Assigning Codes

Developing codes for the data helps simplify the data analysis methods in qualitative research. Assigning code implies categorizing and setting patterns and properties to the collected data. It helps in compressing the vast amount of information collected. By developing codes for your data, you can gather deep insight into the data to make informed business decisions.

4. Analyzing the Data

Qualitative data cannot be analyzed based on any universally accepted equation like quantitative data. Qualitative data analysis depends on the thinking and logical skill of the researcher.

However, there are a few techniques by which you can easily interpret data by identifying themes and patterns between sample responses:

• Checking the data for repetitive words and phrases commonly used by the audience in their answers.
• Comparing the primary and secondary data collection to find the difference between them.
• Scanning the data for expected information that has not been included in answers provided by respondents.

5. Summarizing the Data

The final stage is to link the qualitative data to the hypothesis. Highlight significant themes, patterns, and trends by using essential quotes from the data, as well as any possible contradictions.

One of the main things about qualitative data is that there isn’t a single, formal way to collect and analyze data. Each research project will have its own set of methods and techniques that it needs to use.

The key is to look at the specific needs of each project and change the research method accordingly.

Advantages and Limitations of Qualitative Research

Qualitative market research techniques offer a more comprehensive and complete picture of the subject than quantitative research, which focuses on specific and narrow areas. Other advantages of using qualitative research methods are:

• Explore the subject in-depth: Qualitative research is personal and offers a deep understanding of the respondent’s feelings, thoughts, and actions so that the researcher can perform an in-depth analysis of the subject.
• Promotes discussion: Qualitative research methods are open-ended in approach rather than rigorously following a predetermined set of questions. It adds context to the research rather than just numbers.
• More flexibility: The interviewer can study and ask questions on the subject they feel is pertinent or had not previously thought about during the discussions. Moreover, open-ended questions enable respondents to be free to share their thoughts, leading to more information.
• Capture trends as they change: Qualitative research can track how people’s feelings and attitudes change over time. Respondents’ opinions can change during the conversation, and qualitative research can show this.

With that being said, however, we do not mean that qualitative data is entirely devoid of flaws. Like most things, it, too, has its fair share of limitations, the prime among them being:

• Subjectivity: Qualitative data can be influenced by the researcher’s bias or interpretation, potentially affecting the objectivity of the findings. The absence of strict guidelines in qualitative research can lead to variations in data collection and analysis too.
• Time-Consuming & Resource-Intensive: Conducting qualitative research can be a lengthy process, from data collection through transcription and analysis. It also often requires skilled researchers, making it more resource-intensive compared to some quantitative methods.
• Difficulty in Analysis: Analyzing qualitative data can be complex, as it involves coding, categorizing, and interpreting open-ended responses. This data category often does not lend itself well to traditional statistical tests, limiting the depth of statistical analysis as well.
• Challenges in Replication: Replicating qualitative studies can be challenging due to the unique context and interactions involved.

Advantages of Using Website Surveys for Qualitative Research

The role of surveys and questionnaires in collecting quantitative data is pretty obvious, but how exactly would you use them to capture qualitative data, and why? Well, for starters, website surveys offer numerous advantages here, such as letting researchers explore diverse perspectives, collect rich and detailed data, conduct cost-effective and time-efficient studies, etc.

Let’s have a brief rundown of the significant benefits below:

Reach and Diversity: Website surveys enable researchers to engage with a diverse and global audience. They break geographical barriers, allowing participation from individuals residing in different regions, cultures, and backgrounds, leading to a richer pool of perspectives.

• Cost-Effectiveness: Conducting traditional face-to-face qualitative research can be expensive and time-consuming. In contrast, website surveys are cost-effective, as they eliminate the need for travel, venue rentals, and other logistical expenses.
• Convenience and Flexibility: Website surveys offer unparalleled convenience to both researchers and participants. Respondents can take part in the study at their own pace and preferred time, promoting higher response rates and reducing non-response bias.
• Anonymity and Honesty: Participants often feel more comfortable expressing themselves honestly in online surveys. Anonymity ensures confidentiality, encouraging candid responses, and allowing researchers to gain deeper insights into personal experiences and opinions.
• Rich Data Collection: Website surveys can accommodate various question types, including open-ended questions, allowing respondents to elaborate on their thoughts. This results in the collection of rich, detailed, and nuanced data, enriching the qualitative analysis.
• Time-Efficient Data Collection: Website surveys facilitate efficient data collection, reaching a large number of participants in a short span. Researchers can access real-time data, enabling quick analysis and timely decision-making.
• Ease of Analysis: Online survey platforms often provide tools for automated data analysis, simplifying the coding and categorization process. Researchers can swiftly identify themes and patterns, expediting the interpretation of qualitative findings.
• Longitudinal Studies: Website surveys are well-suited for longitudinal studies, as they allow researchers to follow up with the same participants over an extended period. This longitudinal approach enables the exploration of changes in attitudes or behaviors over time.
• Integration with Multimedia: Website surveys can seamlessly incorporate multimedia elements, such as images, videos, or audio clips, enabling respondents to provide more context and depth to their responses.
• Eco-Friendly Approach: By reducing the need for paper and physical materials, website surveys promote a sustainable and eco-friendly approach to data collection, aligning with responsible research practices.

Most website survey tools are equipped with features that efficiently collect and analyze diverse perspectives, ultimately furthering your data collection process. For example:

• Question Customization: These tools allow users to create and customize a wide range of questions, including open-ended, closed-ended, rating scale, and more. This flexibility allows participants to express their thoughts and feelings in their own words, paving the way for gathering diverse qualitative data.
• Anonymity and Confidentiality: Ensuring confidentiality in qualitative research is crucial for building trust and obtaining more accurate and sensitive data. Participants can often remain anonymous when using website survey tools, which can encourage them to provide honest and candid responses.
• Data Analysis Support: Many website survey tools offer built-in data analysis features, such as basic statistical summaries and visualizations. While these features are more suited for quantitative data, they can still aid in organizing and understanding qualitative responses, making the analysis process more manageable.
• Flexibility in Survey Design: Researchers can use skip logic and branching features in these tools to create dynamic surveys that adapt based on participants’ responses. This can be greatly valuable in qualitative research, where participants’ experiences might vary widely.
• Ease of Participation: Participants can access website surveys using various devices like computers, tablets, or smartphones, making it convenient and accessible for them to take part in the research. This ease of participation can contribute to a higher response rate and a more diverse participant pool.
• Data Storage and Security: Many website survey tools offer secure data storage and backup, ensuring the safety of the collected qualitative data. This feature is essential for maintaining the confidentiality and integrity of participants’ responses.

Examples of Website Survey Questions for Qualitative Research

Crafting effective survey questions is crucial for qualitative research. Ensuring clarity, avoiding leading questions, and maintaining a balanced mix of question types is paramount if you are looking to gather comprehensive and valuable qualitative data.

With well-designed website survey questions, you can delve deep into participants’ thoughts, emotions, and experiences, providing a solid foundation for insightful qualitative analysis.

Let’s explore some of the prime examples:

1. Open-Ended Questions (Exploratory):

• “Please describe your experience with our product/service in your own words.”
• “What are the main challenges you face in your daily work?”

2. Multiple-Choice Questions (Categorization):

“Which age group do you belong to?”

• 18-25 years
• 26-35 years
• 36-45 years
• 46-55 years

3. Likert Scale Questions (Rating/Opinion): “On a scale of 1 to 5, how satisfied are you with our customer support?” 1 (Not satisfied at all) 2 (Slightly satisfied) 3 (Moderately satisfied) 4 (Very satisfied) 5 (Extremely satisfied)

4. Ranking Questions (Preference):

“Please rank the following factors in order of importance for choosing a smartphone:”

• Battery life
• Camera quality
• Processor speed
• Display resolution

5. Semantic Differential Questions (Contrast): “How would you describe our website’s user interface?”

• Difficult _ Easy Unattractive Attractive
• Confusing ___ Clear

6. Picture Choice Questions (Visual Feedback):

“Which logo do you find more appealing for our brand?”

• Option A (Image)
• Option B (Image)

7. Demographic Questions (Participant Profiling):

“Which of the following best describes your occupation?”

• Professional

8. Dichotomous Questions (Yes/No):

• “Have you ever purchased products from our online store?”

9. Follow-Up Probing Questions (In-depth Insight):

• “You mentioned facing challenges at work. Could you please elaborate on the specific challenges you encounter?”

10. Experience-Based Questions (Narrative):

• “Tell us about a memorable customer service experience you’ve had, whether positive or negative.”

Ready to Obtain Quality Data Using Qualitative Research?

So, there you have it all about qualitative research methods: their types, examples, use, and importance. Quantitative research is one of the most effective instruments to understand individuals’ thoughts and feelings or identify their needs and problems.

After figuring out the problem, quantitative research is used to make the conclusion and offer a reliable solution for business.

You can also supplement your qualitative market research with ProProfs Survey Maker to reach your target audience more effectively and in a shorter duration. Use the 15-day free trial to enhance your qualitative research – no commitment, no credit card details!

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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Chapter 1. Introduction

“Science is in danger, and for that reason it is becoming dangerous” -Pierre Bourdieu, Science of Science and Reflexivity

Why an Open Access Textbook on Qualitative Research Methods?

I have been teaching qualitative research methods to both undergraduates and graduate students for many years.  Although there are some excellent textbooks out there, they are often costly, and none of them, to my mind, properly introduces qualitative research methods to the beginning student (whether undergraduate or graduate student).  In contrast, this open-access textbook is designed as a (free) true introduction to the subject, with helpful, practical pointers on how to conduct research and how to access more advanced instruction.  

Textbooks are typically arranged in one of two ways: (1) by technique (each chapter covers one method used in qualitative research); or (2) by process (chapters advance from research design through publication).  But both of these approaches are necessary for the beginner student.  This textbook will have sections dedicated to the process as well as the techniques of qualitative research.  This is a true “comprehensive” book for the beginning student.  In addition to covering techniques of data collection and data analysis, it provides a road map of how to get started and how to keep going and where to go for advanced instruction.  It covers aspects of research design and research communication as well as methods employed.  Along the way, it includes examples from many different disciplines in the social sciences.

The primary goal has been to create a useful, accessible, engaging textbook for use across many disciplines.  And, let’s face it.  Textbooks can be boring.  I hope readers find this to be a little different.  I have tried to write in a practical and forthright manner, with many lively examples and references to good and intellectually creative qualitative research.  Woven throughout the text are short textual asides (in colored textboxes) by professional (academic) qualitative researchers in various disciplines.  These short accounts by practitioners should help inspire students.  So, let’s begin!

What is Research?

When we use the word research , what exactly do we mean by that?  This is one of those words that everyone thinks they understand, but it is worth beginning this textbook with a short explanation.  We use the term to refer to “empirical research,” which is actually a historically specific approach to understanding the world around us.  Think about how you know things about the world. [1] You might know your mother loves you because she’s told you she does.  Or because that is what “mothers” do by tradition.  Or you might know because you’ve looked for evidence that she does, like taking care of you when you are sick or reading to you in bed or working two jobs so you can have the things you need to do OK in life.  Maybe it seems churlish to look for evidence; you just take it “on faith” that you are loved.

Only one of the above comes close to what we mean by research.  Empirical research is research (investigation) based on evidence.  Conclusions can then be drawn from observable data.  This observable data can also be “tested” or checked.  If the data cannot be tested, that is a good indication that we are not doing research.  Note that we can never “prove” conclusively, through observable data, that our mothers love us.  We might have some “disconfirming evidence” (that time she didn’t show up to your graduation, for example) that could push you to question an original hypothesis , but no amount of “confirming evidence” will ever allow us to say with 100% certainty, “my mother loves me.”  Faith and tradition and authority work differently.  Our knowledge can be 100% certain using each of those alternative methods of knowledge, but our certainty in those cases will not be based on facts or evidence.

For many periods of history, those in power have been nervous about “science” because it uses evidence and facts as the primary source of understanding the world, and facts can be at odds with what power or authority or tradition want you to believe.  That is why I say that scientific empirical research is a historically specific approach to understand the world.  You are in college or university now partly to learn how to engage in this historically specific approach.

In the sixteenth and seventeenth centuries in Europe, there was a newfound respect for empirical research, some of which was seriously challenging to the established church.  Using observations and testing them, scientists found that the earth was not at the center of the universe, for example, but rather that it was but one planet of many which circled the sun. [2]   For the next two centuries, the science of astronomy, physics, biology, and chemistry emerged and became disciplines taught in universities.  All used the scientific method of observation and testing to advance knowledge.  Knowledge about people , however, and social institutions, however, was still left to faith, tradition, and authority.  Historians and philosophers and poets wrote about the human condition, but none of them used research to do so. [3]

It was not until the nineteenth century that “social science” really emerged, using the scientific method (empirical observation) to understand people and social institutions.  New fields of sociology, economics, political science, and anthropology emerged.  The first sociologists, people like Auguste Comte and Karl Marx, sought specifically to apply the scientific method of research to understand society, Engels famously claiming that Marx had done for the social world what Darwin did for the natural world, tracings its laws of development.  Today we tend to take for granted the naturalness of science here, but it is actually a pretty recent and radical development.

To return to the question, “does your mother love you?”  Well, this is actually not really how a researcher would frame the question, as it is too specific to your case.  It doesn’t tell us much about the world at large, even if it does tell us something about you and your relationship with your mother.  A social science researcher might ask, “do mothers love their children?”  Or maybe they would be more interested in how this loving relationship might change over time (e.g., “do mothers love their children more now than they did in the 18th century when so many children died before reaching adulthood?”) or perhaps they might be interested in measuring quality of love across cultures or time periods, or even establishing “what love looks like” using the mother/child relationship as a site of exploration.  All of these make good research questions because we can use observable data to answer them.

What is Qualitative Research?

“All we know is how to learn. How to study, how to listen, how to talk, how to tell.  If we don’t tell the world, we don’t know the world.  We’re lost in it, we die.” -Ursula LeGuin, The Telling

At its simplest, qualitative research is research about the social world that does not use numbers in its analyses.  All those who fear statistics can breathe a sigh of relief – there are no mathematical formulae or regression models in this book! But this definition is less about what qualitative research can be and more about what it is not.  To be honest, any simple statement will fail to capture the power and depth of qualitative research.  One way of contrasting qualitative research to quantitative research is to note that the focus of qualitative research is less about explaining and predicting relationships between variables and more about understanding the social world.  To use our mother love example, the question about “what love looks like” is a good question for the qualitative researcher while all questions measuring love or comparing incidences of love (both of which require measurement) are good questions for quantitative researchers. Patton writes,

Qualitative data describe.  They take us, as readers, into the time and place of the observation so that we know what it was like to have been there.  They capture and communicate someone else’s experience of the world in his or her own words.  Qualitative data tell a story. ( Patton 2002:47 )

Qualitative researchers are asking different questions about the world than their quantitative colleagues.  Even when researchers are employed in “mixed methods” research ( both quantitative and qualitative), they are using different methods to address different questions of the study.  I do a lot of research about first-generation and working-college college students.  Where a quantitative researcher might ask, how many first-generation college students graduate from college within four years? Or does first-generation college status predict high student debt loads?  A qualitative researcher might ask, how does the college experience differ for first-generation college students?  What is it like to carry a lot of debt, and how does this impact the ability to complete college on time?  Both sets of questions are important, but they can only be answered using specific tools tailored to those questions.  For the former, you need large numbers to make adequate comparisons.  For the latter, you need to talk to people, find out what they are thinking and feeling, and try to inhabit their shoes for a little while so you can make sense of their experiences and beliefs.

Examples of Qualitative Research

You have probably seen examples of qualitative research before, but you might not have paid particular attention to how they were produced or realized that the accounts you were reading were the result of hours, months, even years of research “in the field.”  A good qualitative researcher will present the product of their hours of work in such a way that it seems natural, even obvious, to the reader.  Because we are trying to convey what it is like answers, qualitative research is often presented as stories – stories about how people live their lives, go to work, raise their children, interact with one another.  In some ways, this can seem like reading particularly insightful novels.  But, unlike novels, there are very specific rules and guidelines that qualitative researchers follow to ensure that the “story” they are telling is accurate , a truthful rendition of what life is like for the people being studied.  Most of this textbook will be spent conveying those rules and guidelines.  Let’s take a look, first, however, at three examples of what the end product looks like.  I have chosen these three examples to showcase very different approaches to qualitative research, and I will return to these five examples throughout the book.  They were all published as whole books (not chapters or articles), and they are worth the long read, if you have the time.  I will also provide some information on how these books came to be and the length of time it takes to get them into book version.  It is important you know about this process, and the rest of this textbook will help explain why it takes so long to conduct good qualitative research!

Example 1 : The End Game (ethnography + interviews)

Corey Abramson is a sociologist who teaches at the University of Arizona.   In 2015 he published The End Game: How Inequality Shapes our Final Years ( 2015 ). This book was based on the research he did for his dissertation at the University of California-Berkeley in 2012.  Actually, the dissertation was completed in 2012 but the work that was produced that took several years.  The dissertation was entitled, “This is How We Live, This is How We Die: Social Stratification, Aging, and Health in Urban America” ( 2012 ).  You can see how the book version, which was written for a more general audience, has a more engaging sound to it, but that the dissertation version, which is what academic faculty read and evaluate, has a more descriptive title.  You can read the title and know that this is a study about aging and health and that the focus is going to be inequality and that the context (place) is going to be “urban America.”  It’s a study about “how” people do something – in this case, how they deal with aging and death.  This is the very first sentence of the dissertation, “From our first breath in the hospital to the day we die, we live in a society characterized by unequal opportunities for maintaining health and taking care of ourselves when ill.  These disparities reflect persistent racial, socio-economic, and gender-based inequalities and contribute to their persistence over time” ( 1 ).  What follows is a truthful account of how that is so.

Cory Abramson spent three years conducting his research in four different urban neighborhoods.  We call the type of research he conducted “comparative ethnographic” because he designed his study to compare groups of seniors as they went about their everyday business.  It’s comparative because he is comparing different groups (based on race, class, gender) and ethnographic because he is studying the culture/way of life of a group. [4]   He had an educated guess, rooted in what previous research had shown and what social theory would suggest, that people’s experiences of aging differ by race, class, and gender.  So, he set up a research design that would allow him to observe differences.  He chose two primarily middle-class (one was racially diverse and the other was predominantly White) and two primarily poor neighborhoods (one was racially diverse and the other was predominantly African American).  He hung out in senior centers and other places seniors congregated, watched them as they took the bus to get prescriptions filled, sat in doctor’s offices with them, and listened to their conversations with each other.  He also conducted more formal conversations, what we call in-depth interviews, with sixty seniors from each of the four neighborhoods.  As with a lot of fieldwork , as he got closer to the people involved, he both expanded and deepened his reach –

By the end of the project, I expanded my pool of general observations to include various settings frequented by seniors: apartment building common rooms, doctors’ offices, emergency rooms, pharmacies, senior centers, bars, parks, corner stores, shopping centers, pool halls, hair salons, coffee shops, and discount stores. Over the course of the three years of fieldwork, I observed hundreds of elders, and developed close relationships with a number of them. ( 2012:10 )

When Abramson rewrote the dissertation for a general audience and published his book in 2015, it got a lot of attention.  It is a beautifully written book and it provided insight into a common human experience that we surprisingly know very little about.  It won the Outstanding Publication Award by the American Sociological Association Section on Aging and the Life Course and was featured in the New York Times .  The book was about aging, and specifically how inequality shapes the aging process, but it was also about much more than that.  It helped show how inequality affects people’s everyday lives.  For example, by observing the difficulties the poor had in setting up appointments and getting to them using public transportation and then being made to wait to see a doctor, sometimes in standing-room-only situations, when they are unwell, and then being treated dismissively by hospital staff, Abramson allowed readers to feel the material reality of being poor in the US.  Comparing these examples with seniors with adequate supplemental insurance who have the resources to hire car services or have others assist them in arranging care when they need it, jolts the reader to understand and appreciate the difference money makes in the lives and circumstances of us all, and in a way that is different than simply reading a statistic (“80% of the poor do not keep regular doctor’s appointments”) does.  Qualitative research can reach into spaces and places that often go unexamined and then reports back to the rest of us what it is like in those spaces and places.

Example 2: Racing for Innocence (Interviews + Content Analysis + Fictional Stories)

Jennifer Pierce is a Professor of American Studies at the University of Minnesota.  Trained as a sociologist, she has written a number of books about gender, race, and power.  Her very first book, Gender Trials: Emotional Lives in Contemporary Law Firms, published in 1995, is a brilliant look at gender dynamics within two law firms.  Pierce was a participant observer, working as a paralegal, and she observed how female lawyers and female paralegals struggled to obtain parity with their male colleagues.

Fifteen years later, she reexamined the context of the law firm to include an examination of racial dynamics, particularly how elite white men working in these spaces created and maintained a culture that made it difficult for both female attorneys and attorneys of color to thrive. Her book, Racing for Innocence: Whiteness, Gender, and the Backlash Against Affirmative Action , published in 2012, is an interesting and creative blending of interviews with attorneys, content analyses of popular films during this period, and fictional accounts of racial discrimination and sexual harassment.  The law firm she chose to study had come under an affirmative action order and was in the process of implementing equitable policies and programs.  She wanted to understand how recipients of white privilege (the elite white male attorneys) come to deny the role they play in reproducing inequality.  Through interviews with attorneys who were present both before and during the affirmative action order, she creates a historical record of the “bad behavior” that necessitated new policies and procedures, but also, and more importantly , probed the participants ’ understanding of this behavior.  It should come as no surprise that most (but not all) of the white male attorneys saw little need for change, and that almost everyone else had accounts that were different if not sometimes downright harrowing.

I’ve used Pierce’s book in my qualitative research methods courses as an example of an interesting blend of techniques and presentation styles.  My students often have a very difficult time with the fictional accounts she includes.  But they serve an important communicative purpose here.  They are her attempts at presenting “both sides” to an objective reality – something happens (Pierce writes this something so it is very clear what it is), and the two participants to the thing that happened have very different understandings of what this means.  By including these stories, Pierce presents one of her key findings – people remember things differently and these different memories tend to support their own ideological positions.  I wonder what Pierce would have written had she studied the murder of George Floyd or the storming of the US Capitol on January 6 or any number of other historic events whose observers and participants record very different happenings.

This is not to say that qualitative researchers write fictional accounts.  In fact, the use of fiction in our work remains controversial.  When used, it must be clearly identified as a presentation device, as Pierce did.  I include Racing for Innocence here as an example of the multiple uses of methods and techniques and the way that these work together to produce better understandings by us, the readers, of what Pierce studied.  We readers come away with a better grasp of how and why advantaged people understate their own involvement in situations and structures that advantage them.  This is normal human behavior , in other words.  This case may have been about elite white men in law firms, but the general insights here can be transposed to other settings.  Indeed, Pierce argues that more research needs to be done about the role elites play in the reproduction of inequality in the workplace in general.

Example 3: Amplified Advantage (Mixed Methods: Survey Interviews + Focus Groups + Archives)

The final example comes from my own work with college students, particularly the ways in which class background affects the experience of college and outcomes for graduates.  I include it here as an example of mixed methods, and for the use of supplementary archival research.  I’ve done a lot of research over the years on first-generation, low-income, and working-class college students.  I am curious (and skeptical) about the possibility of social mobility today, particularly with the rising cost of college and growing inequality in general.  As one of the few people in my family to go to college, I didn’t grow up with a lot of examples of what college was like or how to make the most of it.  And when I entered graduate school, I realized with dismay that there were very few people like me there.  I worried about becoming too different from my family and friends back home.  And I wasn’t at all sure that I would ever be able to pay back the huge load of debt I was taking on.  And so I wrote my dissertation and first two books about working-class college students.  These books focused on experiences in college and the difficulties of navigating between family and school ( Hurst 2010a, 2012 ).  But even after all that research, I kept coming back to wondering if working-class students who made it through college had an equal chance at finding good jobs and happy lives,

What happens to students after college?  Do working-class students fare as well as their peers?  I knew from my own experience that barriers continued through graduate school and beyond, and that my debtload was higher than that of my peers, constraining some of the choices I made when I graduated.  To answer these questions, I designed a study of students attending small liberal arts colleges, the type of college that tried to equalize the experience of students by requiring all students to live on campus and offering small classes with lots of interaction with faculty.  These private colleges tend to have more money and resources so they can provide financial aid to low-income students.  They also attract some very wealthy students.  Because they enroll students across the class spectrum, I would be able to draw comparisons.  I ended up spending about four years collecting data, both a survey of more than 2000 students (which formed the basis for quantitative analyses) and qualitative data collection (interviews, focus groups, archival research, and participant observation).  This is what we call a “mixed methods” approach because we use both quantitative and qualitative data.  The survey gave me a large enough number of students that I could make comparisons of the how many kind, and to be able to say with some authority that there were in fact significant differences in experience and outcome by class (e.g., wealthier students earned more money and had little debt; working-class students often found jobs that were not in their chosen careers and were very affected by debt, upper-middle-class students were more likely to go to graduate school).  But the survey analyses could not explain why these differences existed.  For that, I needed to talk to people and ask them about their motivations and aspirations.  I needed to understand their perceptions of the world, and it is very hard to do this through a survey.

By interviewing students and recent graduates, I was able to discern particular patterns and pathways through college and beyond.  Specifically, I identified three versions of gameplay.  Upper-middle-class students, whose parents were themselves professionals (academics, lawyers, managers of non-profits), saw college as the first stage of their education and took classes and declared majors that would prepare them for graduate school.  They also spent a lot of time building their resumes, taking advantage of opportunities to help professors with their research, or study abroad.  This helped them gain admission to highly-ranked graduate schools and interesting jobs in the public sector.  In contrast, upper-class students, whose parents were wealthy and more likely to be engaged in business (as CEOs or other high-level directors), prioritized building social capital.  They did this by joining fraternities and sororities and playing club sports.  This helped them when they graduated as they called on friends and parents of friends to find them well-paying jobs.  Finally, low-income, first-generation, and working-class students were often adrift.  They took the classes that were recommended to them but without the knowledge of how to connect them to life beyond college.  They spent time working and studying rather than partying or building their resumes.  All three sets of students thought they were “doing college” the right way, the way that one was supposed to do college.   But these three versions of gameplay led to distinct outcomes that advantaged some students over others.  I titled my work “Amplified Advantage” to highlight this process.

These three examples, Cory Abramson’s The End Game , Jennifer Peirce’s Racing for Innocence, and my own Amplified Advantage, demonstrate the range of approaches and tools available to the qualitative researcher.  They also help explain why qualitative research is so important.  Numbers can tell us some things about the world, but they cannot get at the hearts and minds, motivations and beliefs of the people who make up the social worlds we inhabit.  For that, we need tools that allow us to listen and make sense of what people tell us and show us.  That is what good qualitative research offers us.

How Is This Book Organized?

This textbook is organized as a comprehensive introduction to the use of qualitative research methods.  The first half covers general topics (e.g., approaches to qualitative research, ethics) and research design (necessary steps for building a successful qualitative research study).  The second half reviews various data collection and data analysis techniques.  Of course, building a successful qualitative research study requires some knowledge of data collection and data analysis so the chapters in the first half and the chapters in the second half should be read in conversation with each other.  That said, each chapter can be read on its own for assistance with a particular narrow topic.  In addition to the chapters, a helpful glossary can be found in the back of the book.  Rummage around in the text as needed.

Chapter Descriptions

Chapter 2 provides an overview of the Research Design Process.  How does one begin a study? What is an appropriate research question?  How is the study to be done – with what methods ?  Involving what people and sites?  Although qualitative research studies can and often do change and develop over the course of data collection, it is important to have a good idea of what the aims and goals of your study are at the outset and a good plan of how to achieve those aims and goals.  Chapter 2 provides a road map of the process.

Chapter 3 describes and explains various ways of knowing the (social) world.  What is it possible for us to know about how other people think or why they behave the way they do?  What does it mean to say something is a “fact” or that it is “well-known” and understood?  Qualitative researchers are particularly interested in these questions because of the types of research questions we are interested in answering (the how questions rather than the how many questions of quantitative research).  Qualitative researchers have adopted various epistemological approaches.  Chapter 3 will explore these approaches, highlighting interpretivist approaches that acknowledge the subjective aspect of reality – in other words, reality and knowledge are not objective but rather influenced by (interpreted through) people.

Chapter 4 focuses on the practical matter of developing a research question and finding the right approach to data collection.  In any given study (think of Cory Abramson’s study of aging, for example), there may be years of collected data, thousands of observations , hundreds of pages of notes to read and review and make sense of.  If all you had was a general interest area (“aging”), it would be very difficult, nearly impossible, to make sense of all of that data.  The research question provides a helpful lens to refine and clarify (and simplify) everything you find and collect.  For that reason, it is important to pull out that lens (articulate the research question) before you get started.  In the case of the aging study, Cory Abramson was interested in how inequalities affected understandings and responses to aging.  It is for this reason he designed a study that would allow him to compare different groups of seniors (some middle-class, some poor).  Inevitably, he saw much more in the three years in the field than what made it into his book (or dissertation), but he was able to narrow down the complexity of the social world to provide us with this rich account linked to the original research question.  Developing a good research question is thus crucial to effective design and a successful outcome.  Chapter 4 will provide pointers on how to do this.  Chapter 4 also provides an overview of general approaches taken to doing qualitative research and various “traditions of inquiry.”

Chapter 5 explores sampling .  After you have developed a research question and have a general idea of how you will collect data (Observations?  Interviews?), how do you go about actually finding people and sites to study?  Although there is no “correct number” of people to interview , the sample should follow the research question and research design.  Unlike quantitative research, qualitative research involves nonprobability sampling.  Chapter 5 explains why this is so and what qualities instead make a good sample for qualitative research.

Chapter 6 addresses the importance of reflexivity in qualitative research.  Related to epistemological issues of how we know anything about the social world, qualitative researchers understand that we the researchers can never be truly neutral or outside the study we are conducting.  As observers, we see things that make sense to us and may entirely miss what is either too obvious to note or too different to comprehend.  As interviewers, as much as we would like to ask questions neutrally and remain in the background, interviews are a form of conversation, and the persons we interview are responding to us .  Therefore, it is important to reflect upon our social positions and the knowledges and expectations we bring to our work and to work through any blind spots that we may have.  Chapter 6 provides some examples of reflexivity in practice and exercises for thinking through one’s own biases.

Chapter 7 is a very important chapter and should not be overlooked.  As a practical matter, it should also be read closely with chapters 6 and 8.  Because qualitative researchers deal with people and the social world, it is imperative they develop and adhere to a strong ethical code for conducting research in a way that does not harm.  There are legal requirements and guidelines for doing so (see chapter 8), but these requirements should not be considered synonymous with the ethical code required of us.   Each researcher must constantly interrogate every aspect of their research, from research question to design to sample through analysis and presentation, to ensure that a minimum of harm (ideally, zero harm) is caused.  Because each research project is unique, the standards of care for each study are unique.  Part of being a professional researcher is carrying this code in one’s heart, being constantly attentive to what is required under particular circumstances.  Chapter 7 provides various research scenarios and asks readers to weigh in on the suitability and appropriateness of the research.  If done in a class setting, it will become obvious fairly quickly that there are often no absolutely correct answers, as different people find different aspects of the scenarios of greatest importance.  Minimizing the harm in one area may require possible harm in another.  Being attentive to all the ethical aspects of one’s research and making the best judgments one can, clearly and consciously, is an integral part of being a good researcher.

Chapter 8 , best to be read in conjunction with chapter 7, explains the role and importance of Institutional Review Boards (IRBs) .  Under federal guidelines, an IRB is an appropriately constituted group that has been formally designated to review and monitor research involving human subjects .  Every institution that receives funding from the federal government has an IRB.  IRBs have the authority to approve, require modifications to (to secure approval), or disapprove research.  This group review serves an important role in the protection of the rights and welfare of human research subjects.  Chapter 8 reviews the history of IRBs and the work they do but also argues that IRBs’ review of qualitative research is often both over-inclusive and under-inclusive.  Some aspects of qualitative research are not well understood by IRBs, given that they were developed to prevent abuses in biomedical research.  Thus, it is important not to rely on IRBs to identify all the potential ethical issues that emerge in our research (see chapter 7).

Chapter 9 provides help for getting started on formulating a research question based on gaps in the pre-existing literature.  Research is conducted as part of a community, even if particular studies are done by single individuals (or small teams).  What any of us finds and reports back becomes part of a much larger body of knowledge.  Thus, it is important that we look at the larger body of knowledge before we actually start our bit to see how we can best contribute.  When I first began interviewing working-class college students, there was only one other similar study I could find, and it hadn’t been published (it was a dissertation of students from poor backgrounds).  But there had been a lot published by professors who had grown up working class and made it through college despite the odds.  These accounts by “working-class academics” became an important inspiration for my study and helped me frame the questions I asked the students I interviewed.  Chapter 9 will provide some pointers on how to search for relevant literature and how to use this to refine your research question.

Chapter 10 serves as a bridge between the two parts of the textbook, by introducing techniques of data collection.  Qualitative research is often characterized by the form of data collection – for example, an ethnographic study is one that employs primarily observational data collection for the purpose of documenting and presenting a particular culture or ethnos.  Techniques can be effectively combined, depending on the research question and the aims and goals of the study.   Chapter 10 provides a general overview of all the various techniques and how they can be combined.

The second part of the textbook moves into the doing part of qualitative research once the research question has been articulated and the study designed.  Chapters 11 through 17 cover various data collection techniques and approaches.  Chapters 18 and 19 provide a very simple overview of basic data analysis.  Chapter 20 covers communication of the data to various audiences, and in various formats.

Chapter 11 begins our overview of data collection techniques with a focus on interviewing , the true heart of qualitative research.  This technique can serve as the primary and exclusive form of data collection, or it can be used to supplement other forms (observation, archival).  An interview is distinct from a survey, where questions are asked in a specific order and often with a range of predetermined responses available.  Interviews can be conversational and unstructured or, more conventionally, semistructured , where a general set of interview questions “guides” the conversation.  Chapter 11 covers the basics of interviews: how to create interview guides, how many people to interview, where to conduct the interview, what to watch out for (how to prepare against things going wrong), and how to get the most out of your interviews.

Chapter 12 covers an important variant of interviewing, the focus group.  Focus groups are semistructured interviews with a group of people moderated by a facilitator (the researcher or researcher’s assistant).  Focus groups explicitly use group interaction to assist in the data collection.  They are best used to collect data on a specific topic that is non-personal and shared among the group.  For example, asking a group of college students about a common experience such as taking classes by remote delivery during the pandemic year of 2020.  Chapter 12 covers the basics of focus groups: when to use them, how to create interview guides for them, and how to run them effectively.

Chapter 13 moves away from interviewing to the second major form of data collection unique to qualitative researchers – observation .  Qualitative research that employs observation can best be understood as falling on a continuum of “fly on the wall” observation (e.g., observing how strangers interact in a doctor’s waiting room) to “participant” observation, where the researcher is also an active participant of the activity being observed.  For example, an activist in the Black Lives Matter movement might want to study the movement, using her inside position to gain access to observe key meetings and interactions.  Chapter  13 covers the basics of participant observation studies: advantages and disadvantages, gaining access, ethical concerns related to insider/outsider status and entanglement, and recording techniques.

Chapter 14 takes a closer look at “deep ethnography” – immersion in the field of a particularly long duration for the purpose of gaining a deeper understanding and appreciation of a particular culture or social world.  Clifford Geertz called this “deep hanging out.”  Whereas participant observation is often combined with semistructured interview techniques, deep ethnography’s commitment to “living the life” or experiencing the situation as it really is demands more conversational and natural interactions with people.  These interactions and conversations may take place over months or even years.  As can be expected, there are some costs to this technique, as well as some very large rewards when done competently.  Chapter 14 provides some examples of deep ethnographies that will inspire some beginning researchers and intimidate others.

Chapter 15 moves in the opposite direction of deep ethnography, a technique that is the least positivist of all those discussed here, to mixed methods , a set of techniques that is arguably the most positivist .  A mixed methods approach combines both qualitative data collection and quantitative data collection, commonly by combining a survey that is analyzed statistically (e.g., cross-tabs or regression analyses of large number probability samples) with semi-structured interviews.  Although it is somewhat unconventional to discuss mixed methods in textbooks on qualitative research, I think it is important to recognize this often-employed approach here.  There are several advantages and some disadvantages to taking this route.  Chapter 16 will describe those advantages and disadvantages and provide some particular guidance on how to design a mixed methods study for maximum effectiveness.

Chapter 16 covers data collection that does not involve live human subjects at all – archival and historical research (chapter 17 will also cover data that does not involve interacting with human subjects).  Sometimes people are unavailable to us, either because they do not wish to be interviewed or observed (as is the case with many “elites”) or because they are too far away, in both place and time.  Fortunately, humans leave many traces and we can often answer questions we have by examining those traces.  Special collections and archives can be goldmines for social science research.  This chapter will explain how to access these places, for what purposes, and how to begin to make sense of what you find.

Chapter 17 covers another data collection area that does not involve face-to-face interaction with humans: content analysis .  Although content analysis may be understood more properly as a data analysis technique, the term is often used for the entire approach, which will be the case here.  Content analysis involves interpreting meaning from a body of text.  This body of text might be something found in historical records (see chapter 16) or something collected by the researcher, as in the case of comment posts on a popular blog post.  I once used the stories told by student loan debtors on the website studentloanjustice.org as the content I analyzed.  Content analysis is particularly useful when attempting to define and understand prevalent stories or communication about a topic of interest.  In other words, when we are less interested in what particular people (our defined sample) are doing or believing and more interested in what general narratives exist about a particular topic or issue.  This chapter will explore different approaches to content analysis and provide helpful tips on how to collect data, how to turn that data into codes for analysis, and how to go about presenting what is found through analysis.

Where chapter 17 has pushed us towards data analysis, chapters 18 and 19 are all about what to do with the data collected, whether that data be in the form of interview transcripts or fieldnotes from observations.  Chapter 18 introduces the basics of coding , the iterative process of assigning meaning to the data in order to both simplify and identify patterns.  What is a code and how does it work?  What are the different ways of coding data, and when should you use them?  What is a codebook, and why do you need one?  What does the process of data analysis look like?

Chapter 19 goes further into detail on codes and how to use them, particularly the later stages of coding in which our codes are refined, simplified, combined, and organized.  These later rounds of coding are essential to getting the most out of the data we’ve collected.  As students are often overwhelmed with the amount of data (a corpus of interview transcripts typically runs into the hundreds of pages; fieldnotes can easily top that), this chapter will also address time management and provide suggestions for dealing with chaos and reminders that feeling overwhelmed at the analysis stage is part of the process.  By the end of the chapter, you should understand how “findings” are actually found.

The book concludes with a chapter dedicated to the effective presentation of data results.  Chapter 20 covers the many ways that researchers communicate their studies to various audiences (academic, personal, political), what elements must be included in these various publications, and the hallmarks of excellent qualitative research that various audiences will be expecting.  Because qualitative researchers are motivated by understanding and conveying meaning , effective communication is not only an essential skill but a fundamental facet of the entire research project.  Ethnographers must be able to convey a certain sense of verisimilitude , the appearance of true reality.  Those employing interviews must faithfully depict the key meanings of the people they interviewed in a way that rings true to those people, even if the end result surprises them.  And all researchers must strive for clarity in their publications so that various audiences can understand what was found and why it is important.

The book concludes with a short chapter ( chapter 21 ) discussing the value of qualitative research. At the very end of this book, you will find a glossary of terms. I recommend you make frequent use of the glossary and add to each entry as you find examples. Although the entries are meant to be simple and clear, you may also want to paraphrase the definition—make it “make sense” to you, in other words. In addition to the standard reference list (all works cited here), you will find various recommendations for further reading at the end of many chapters. Some of these recommendations will be examples of excellent qualitative research, indicated with an asterisk (*) at the end of the entry. As they say, a picture is worth a thousand words. A good example of qualitative research can teach you more about conducting research than any textbook can (this one included). I highly recommend you select one to three examples from these lists and read them along with the textbook.

A final note on the choice of examples – you will note that many of the examples used in the text come from research on college students.  This is for two reasons.  First, as most of my research falls in this area, I am most familiar with this literature and have contacts with those who do research here and can call upon them to share their stories with you.  Second, and more importantly, my hope is that this textbook reaches a wide audience of beginning researchers who study widely and deeply across the range of what can be known about the social world (from marine resources management to public policy to nursing to political science to sexuality studies and beyond).  It is sometimes difficult to find examples that speak to all those research interests, however. A focus on college students is something that all readers can understand and, hopefully, appreciate, as we are all now or have been at some point a college student.

Recommended Reading: Other Qualitative Research Textbooks

I’ve included a brief list of some of my favorite qualitative research textbooks and guidebooks if you need more than what you will find in this introductory text.  For each, I’ve also indicated if these are for “beginning” or “advanced” (graduate-level) readers.  Many of these books have several editions that do not significantly vary; the edition recommended is merely the edition I have used in teaching and to whose page numbers any specific references made in the text agree.

Barbour, Rosaline. 2014. Introducing Qualitative Research: A Student’s Guide. Thousand Oaks, CA: SAGE.  A good introduction to qualitative research, with abundant examples (often from the discipline of health care) and clear definitions.  Includes quick summaries at the ends of each chapter.  However, some US students might find the British context distracting and can be a bit advanced in some places.  Beginning .

Bloomberg, Linda Dale, and Marie F. Volpe. 2012. Completing Your Qualitative Dissertation . 2nd ed. Thousand Oaks, CA: SAGE.  Specifically designed to guide graduate students through the research process. Advanced .

Creswell, John W., and Cheryl Poth. 2018 Qualitative Inquiry and Research Design: Choosing among Five Traditions .  4th ed. Thousand Oaks, CA: SAGE.  This is a classic and one of the go-to books I used myself as a graduate student.  One of the best things about this text is its clear presentation of five distinct traditions in qualitative research.  Despite the title, this reasonably sized book is about more than research design, including both data analysis and how to write about qualitative research.  Advanced .

Lareau, Annette. 2021. Listening to People: A Practical Guide to Interviewing, Participant Observation, Data Analysis, and Writing It All Up .  Chicago: University of Chicago Press. A readable and personal account of conducting qualitative research by an eminent sociologist, with a heavy emphasis on the kinds of participant-observation research conducted by the author.  Despite its reader-friendliness, this is really a book targeted to graduate students learning the craft.  Advanced .

Lune, Howard, and Bruce L. Berg. 2018. 9th edition.  Qualitative Research Methods for the Social Sciences.  Pearson . Although a good introduction to qualitative methods, the authors favor symbolic interactionist and dramaturgical approaches, which limits the appeal primarily to sociologists.  Beginning .

Marshall, Catherine, and Gretchen B. Rossman. 2016. 6th edition. Designing Qualitative Research. Thousand Oaks, CA: SAGE.  Very readable and accessible guide to research design by two educational scholars.  Although the presentation is sometimes fairly dry, personal vignettes and illustrations enliven the text.  Beginning .

Maxwell, Joseph A. 2013. Qualitative Research Design: An Interactive Approach .  3rd ed. Thousand Oaks, CA: SAGE. A short and accessible introduction to qualitative research design, particularly helpful for graduate students contemplating theses and dissertations. This has been a standard textbook in my graduate-level courses for years.  Advanced .

Patton, Michael Quinn. 2002. Qualitative Research and Evaluation Methods . Thousand Oaks, CA: SAGE.  This is a comprehensive text that served as my “go-to” reference when I was a graduate student.  It is particularly helpful for those involved in program evaluation and other forms of evaluation studies and uses examples from a wide range of disciplines.  Advanced .

Rubin, Ashley T. 2021. Rocking Qualitative Social Science: An Irreverent Guide to Rigorous Research. Stanford : Stanford University Press.  A delightful and personal read.  Rubin uses rock climbing as an extended metaphor for learning how to conduct qualitative research.  A bit slanted toward ethnographic and archival methods of data collection, with frequent examples from her own studies in criminology. Beginning .

Weis, Lois, and Michelle Fine. 2000. Speed Bumps: A Student-Friendly Guide to Qualitative Research . New York: Teachers College Press.  Readable and accessibly written in a quasi-conversational style.  Particularly strong in its discussion of ethical issues throughout the qualitative research process.  Not comprehensive, however, and very much tied to ethnographic research.  Although designed for graduate students, this is a recommended read for students of all levels.  Beginning .

Patton’s Ten Suggestions for Doing Qualitative Research

The following ten suggestions were made by Michael Quinn Patton in his massive textbooks Qualitative Research and Evaluations Methods . This book is highly recommended for those of you who want more than an introduction to qualitative methods. It is the book I relied on heavily when I was a graduate student, although it is much easier to “dip into” when necessary than to read through as a whole. Patton is asked for “just one bit of advice” for a graduate student considering using qualitative research methods for their dissertation.  Here are his top ten responses, in short form, heavily paraphrased, and with additional comments and emphases from me:

• Make sure that a qualitative approach fits the research question. The following are the kinds of questions that call out for qualitative methods or where qualitative methods are particularly appropriate: questions about people’s experiences or how they make sense of those experiences; studying a person in their natural environment; researching a phenomenon so unknown that it would be impossible to study it with standardized instruments or other forms of quantitative data collection.
• Study qualitative research by going to the original sources for the design and analysis appropriate to the particular approach you want to take (e.g., read Glaser and Straus if you are using grounded theory )
• Find a dissertation adviser who understands or at least who will support your use of qualitative research methods. You are asking for trouble if your entire committee is populated by quantitative researchers, even if they are all very knowledgeable about the subject or focus of your study (maybe even more so if they are!)
• Really work on design. Doing qualitative research effectively takes a lot of planning.  Even if things are more flexible than in quantitative research, a good design is absolutely essential when starting out.
• Practice data collection techniques, particularly interviewing and observing. There is definitely a set of learned skills here!  Do not expect your first interview to be perfect.  You will continue to grow as a researcher the more interviews you conduct, and you will probably come to understand yourself a bit more in the process, too.  This is not easy, despite what others who don’t work with qualitative methods may assume (and tell you!)
• Have a plan for analysis before you begin data collection. This is often a requirement in IRB protocols , although you can get away with writing something fairly simple.  And even if you are taking an approach, such as grounded theory, that pushes you to remain fairly open-minded during the data collection process, you still want to know what you will be doing with all the data collected – creating a codebook? Writing analytical memos? Comparing cases?  Having a plan in hand will also help prevent you from collecting too much extraneous data.
• Be prepared to confront controversies both within the qualitative research community and between qualitative research and quantitative research. Don’t be naïve about this – qualitative research, particularly some approaches, will be derided by many more “positivist” researchers and audiences.  For example, is an “n” of 1 really sufficient?  Yes!  But not everyone will agree.
• Do not make the mistake of using qualitative research methods because someone told you it was easier, or because you are intimidated by the math required of statistical analyses. Qualitative research is difficult in its own way (and many would claim much more time-consuming than quantitative research).  Do it because you are convinced it is right for your goals, aims, and research questions.
• Find a good support network. This could be a research mentor, or it could be a group of friends or colleagues who are also using qualitative research, or it could be just someone who will listen to you work through all of the issues you will confront out in the field and during the writing process.  Even though qualitative research often involves human subjects, it can be pretty lonely.  A lot of times you will feel like you are working without a net.  You have to create one for yourself.  Take care of yourself.
• And, finally, in the words of Patton, “Prepare to be changed. Looking deeply at other people’s lives will force you to look deeply at yourself.”
• We will actually spend an entire chapter ( chapter 3 ) looking at this question in much more detail! ↵
• Note that this might have been news to Europeans at the time, but many other societies around the world had also come to this conclusion through observation.  There is often a tendency to equate “the scientific revolution” with the European world in which it took place, but this is somewhat misleading. ↵
• Historians are a special case here.  Historians have scrupulously and rigorously investigated the social world, but not for the purpose of understanding general laws about how things work, which is the point of scientific empirical research.  History is often referred to as an idiographic field of study, meaning that it studies things that happened or are happening in themselves and not for general observations or conclusions. ↵
• Don’t worry, we’ll spend more time later in this book unpacking the meaning of ethnography and other terms that are important here.  Note the available glossary ↵

An approach to research that is “multimethod in focus, involving an interpretative, naturalistic approach to its subject matter.  This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them.  Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives." ( Denzin and Lincoln 2005:2 ). Contrast with quantitative research .

In contrast to methodology, methods are more simply the practices and tools used to collect and analyze data.  Examples of common methods in qualitative research are interviews , observations , and documentary analysis .  One’s methodology should connect to one’s choice of methods, of course, but they are distinguishable terms.  See also methodology .

A proposed explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.  The positing of a hypothesis is often the first step in quantitative research but not in qualitative research.  Even when qualitative researchers offer possible explanations in advance of conducting research, they will tend to not use the word “hypothesis” as it conjures up the kind of positivist research they are not conducting.

The foundational question to be addressed by the research study.  This will form the anchor of the research design, collection, and analysis.  Note that in qualitative research, the research question may, and probably will, alter or develop during the course of the research.

An approach to research that collects and analyzes numerical data for the purpose of finding patterns and averages, making predictions, testing causal relationships, and generalizing results to wider populations.  Contrast with qualitative research .

Data collection that takes place in real-world settings, referred to as “the field;” a key component of much Grounded Theory and ethnographic research.  Patton ( 2002 ) calls fieldwork “the central activity of qualitative inquiry” where “‘going into the field’ means having direct and personal contact with people under study in their own environments – getting close to people and situations being studied to personally understand the realities of minutiae of daily life” (48).

The people who are the subjects of a qualitative study.  In interview-based studies, they may be the respondents to the interviewer; for purposes of IRBs, they are often referred to as the human subjects of the research.

The branch of philosophy concerned with knowledge.  For researchers, it is important to recognize and adopt one of the many distinguishing epistemological perspectives as part of our understanding of what questions research can address or fully answer.  See, e.g., constructivism , subjectivism, and  objectivism .

An approach that refutes the possibility of neutrality in social science research.  All research is “guided by a set of beliefs and feelings about the world and how it should be understood and studied” (Denzin and Lincoln 2005: 13).  In contrast to positivism , interpretivism recognizes the social constructedness of reality, and researchers adopting this approach focus on capturing interpretations and understandings people have about the world rather than “the world” as it is (which is a chimera).

The cluster of data-collection tools and techniques that involve observing interactions between people, the behaviors, and practices of individuals (sometimes in contrast to what they say about how they act and behave), and cultures in context.  Observational methods are the key tools employed by ethnographers and Grounded Theory .

Research based on data collected and analyzed by the research (in contrast to secondary “library” research).

The process of selecting people or other units of analysis to represent a larger population. In quantitative research, this representation is taken quite literally, as statistically representative.  In qualitative research, in contrast, sample selection is often made based on potential to generate insight about a particular topic or phenomenon.

A method of data collection in which the researcher asks the participant questions; the answers to these questions are often recorded and transcribed verbatim. There are many different kinds of interviews - see also semistructured interview , structured interview , and unstructured interview .

The specific group of individuals that you will collect data from.  Contrast population.

The practice of being conscious of and reflective upon one’s own social location and presence when conducting research.  Because qualitative research often requires interaction with live humans, failing to take into account how one’s presence and prior expectations and social location affect the data collected and how analyzed may limit the reliability of the findings.  This remains true even when dealing with historical archives and other content.  Who we are matters when asking questions about how people experience the world because we, too, are a part of that world.

The science and practice of right conduct; in research, it is also the delineation of moral obligations towards research participants, communities to which we belong, and communities in which we conduct our research.

An administrative body established to protect the rights and welfare of human research subjects recruited to participate in research activities conducted under the auspices of the institution with which it is affiliated. The IRB is charged with the responsibility of reviewing all research involving human participants. The IRB is concerned with protecting the welfare, rights, and privacy of human subjects. The IRB has the authority to approve, disapprove, monitor, and require modifications in all research activities that fall within its jurisdiction as specified by both the federal regulations and institutional policy.

Research, according to US federal guidelines, that involves “a living individual about whom an investigator (whether professional or student) conducting research:  (1) Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or  (2) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.”

One of the primary methodological traditions of inquiry in qualitative research, ethnography is the study of a group or group culture, largely through observational fieldwork supplemented by interviews. It is a form of fieldwork that may include participant-observation data collection. See chapter 14 for a discussion of deep ethnography. 

A form of interview that follows a standard guide of questions asked, although the order of the questions may change to match the particular needs of each individual interview subject, and probing “follow-up” questions are often added during the course of the interview.  The semi-structured interview is the primary form of interviewing used by qualitative researchers in the social sciences.  It is sometimes referred to as an “in-depth” interview.  See also interview and  interview guide .

A method of observational data collection taking place in a natural setting; a form of fieldwork .  The term encompasses a continuum of relative participation by the researcher (from full participant to “fly-on-the-wall” observer).  This is also sometimes referred to as ethnography , although the latter is characterized by a greater focus on the culture under observation.

A research design that employs both quantitative and qualitative methods, as in the case of a survey supplemented by interviews.

An epistemological perspective that posits the existence of reality through sensory experience similar to empiricism but goes further in denying any non-sensory basis of thought or consciousness.  In the social sciences, the term has roots in the proto-sociologist August Comte, who believed he could discern “laws” of society similar to the laws of natural science (e.g., gravity).  The term has come to mean the kinds of measurable and verifiable science conducted by quantitative researchers and is thus used pejoratively by some qualitative researchers interested in interpretation, consciousness, and human understanding.  Calling someone a “positivist” is often intended as an insult.  See also empiricism and objectivism.

A place or collection containing records, documents, or other materials of historical interest; most universities have an archive of material related to the university’s history, as well as other “special collections” that may be of interest to members of the community.

A method of both data collection and data analysis in which a given content (textual, visual, graphic) is examined systematically and rigorously to identify meanings, themes, patterns and assumptions.  Qualitative content analysis (QCA) is concerned with gathering and interpreting an existing body of material.    

A word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data (Saldaña 2021:5).

Usually a verbatim written record of an interview or focus group discussion.

The primary form of data for fieldwork , participant observation , and ethnography .  These notes, taken by the researcher either during the course of fieldwork or at day’s end, should include as many details as possible on what was observed and what was said.  They should include clear identifiers of date, time, setting, and names (or identifying characteristics) of participants.

The process of labeling and organizing qualitative data to identify different themes and the relationships between them; a way of simplifying data to allow better management and retrieval of key themes and illustrative passages.  See coding frame and  codebook.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction.  This approach was pioneered by the sociologists Glaser and Strauss (1967).  The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences.  Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

A detailed description of any proposed research that involves human subjects for review by IRB.  The protocol serves as the recipe for the conduct of the research activity.  It includes the scientific rationale to justify the conduct of the study, the information necessary to conduct the study, the plan for managing and analyzing the data, and a discussion of the research ethical issues relevant to the research.  Protocols for qualitative research often include interview guides, all documents related to recruitment, informed consent forms, very clear guidelines on the safekeeping of materials collected, and plans for de-identifying transcripts or other data that include personal identifying information.

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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How to write qualitative research questions.

11 min read Here’s how to write effective qualitative research questions for your projects, and why getting it right matters so much.

What is qualitative research?

Qualitative research is a blanket term covering a wide range of research methods and theoretical framing approaches. The unifying factor in all these types of qualitative study is that they deal with data that cannot be counted. Typically this means things like people’s stories, feelings, opinions and emotions , and the meanings they ascribe to their experiences.

Qualitative study is one of two main categories of research, the other being quantitative research. Quantitative research deals with numerical data – that which can be counted and quantified, and which is mostly concerned with trends and patterns in large-scale datasets.

What are research questions?

Research questions are questions you are trying to answer with your research. To put it another way, your research question is the reason for your study, and the beginning point for your research design. There is normally only one research question per study, although if your project is very complex, you may have multiple research questions that are closely linked to one central question.

A good qualitative research question sums up your research objective. It’s a way of expressing the central question of your research, identifying your particular topic and the central issue you are examining.

Research questions are quite different from survey questions, questions used in focus groups or interview questions. A long list of questions is used in these types of study, as opposed to one central question. Additionally, interview or survey questions are asked of participants, whereas research questions are only for the researcher to maintain a clear understanding of the research design.

Research questions are used in both qualitative and quantitative research , although what makes a good research question might vary between the two.

In fact, the type of research questions you are asking can help you decide whether you need to take a quantitative or qualitative approach to your research project.

Discover the fundamentals of qualitative research

Quantitative vs. qualitative research questions

Writing research questions is very important in both qualitative and quantitative research, but the research questions that perform best in the two types of studies are quite different.

Quantitative research questions

Quantitative research questions usually relate to quantities, similarities and differences.

It might reflect the researchers’ interest in determining whether relationships between variables exist, and if so whether they are statistically significant. Or it may focus on establishing differences between things through comparison, and using statistical analysis to determine whether those differences are meaningful or due to chance.

• How much? This kind of research question is one of the simplest. It focuses on quantifying something. For example:

How many Yoruba speakers are there in the state of Maine?

• What is the connection?

This type of quantitative research question examines how one variable affects another.

For example:

How does a low level of sunlight affect the mood scores (1-10) of Antarctic explorers during winter?

• What is the difference? Quantitative research questions in this category identify two categories and measure the difference between them using numerical data.

Do white cats stay cooler than tabby cats in hot weather?

If your research question fits into one of the above categories, you’re probably going to be doing a quantitative study.

Qualitative research questions

Qualitative research questions focus on exploring phenomena, meanings and experiences.

Unlike quantitative research, qualitative research isn’t about finding causal relationships between variables. So although qualitative research questions might touch on topics that involve one variable influencing another, or looking at the difference between things, finding and quantifying those relationships isn’t the primary objective.

In fact, you as a qualitative researcher might end up studying a very similar topic to your colleague who is doing a quantitative study, but your areas of focus will be quite different. Your research methods will also be different – they might include focus groups, ethnography studies, and other kinds of qualitative study.

A few example qualitative research questions:

• What is it like being an Antarctic explorer during winter?
• What are the experiences of Yoruba speakers in the USA?
• How do white cat owners describe their pets?

Qualitative research question types

Marshall and Rossman (1989) identified 4 qualitative research question types, each with its own typical research strategy and methods.

• Exploratory questions

Exploratory questions are used when relatively little is known about the research topic. The process researchers follow when pursuing exploratory questions might involve interviewing participants, holding focus groups, or diving deep with a case study.

• Explanatory questions

With explanatory questions, the research topic is approached with a view to understanding the causes that lie behind phenomena. However, unlike a quantitative project, the focus of explanatory questions is on qualitative analysis of multiple interconnected factors that have influenced a particular group or area, rather than a provable causal link between dependent and independent variables.

• Descriptive questions

As the name suggests, descriptive questions aim to document and record what is happening. In answering descriptive questions , researchers might interact directly with participants with surveys or interviews, as well as using observational studies and ethnography studies that collect data on how participants interact with their wider environment.

• Predictive questions

Predictive questions start from the phenomena of interest and investigate what ramifications it might have in the future. Answering predictive questions may involve looking back as well as forward, with content analysis, questionnaires and studies of non-verbal communication (kinesics).

Why are good qualitative research questions important?

We know research questions are very important. But what makes them so essential? (And is that question a qualitative or quantitative one?)

Getting your qualitative research questions right has a number of benefits.

• It defines your qualitative research project Qualitative research questions definitively nail down the research population, the thing you’re examining, and what the nature of your answer will be.This means you can explain your research project to other people both inside and outside your business or organization. That could be critical when it comes to securing funding for your project, recruiting participants and members of your research team, and ultimately for publishing your results. It can also help you assess right the ethical considerations for your population of study.
• It maintains focus Good qualitative research questions help researchers to stick to the area of focus as they carry out their research. Keeping the research question in mind will help them steer away from tangents during their research or while they are carrying out qualitative research interviews. This holds true whatever the qualitative methods are, whether it’s a focus group, survey, thematic analysis or other type of inquiry.That doesn’t mean the research project can’t morph and change during its execution – sometimes this is acceptable and even welcome – but having a research question helps demarcate the starting point for the research. It can be referred back to if the scope and focus of the project does change.
• It helps make sure your outcomes are achievable

Because qualitative research questions help determine the kind of results you’re going to get, it helps make sure those results are achievable. By formulating good qualitative research questions in advance, you can make sure the things you want to know and the way you’re going to investigate them are grounded in practical reality. Otherwise, you may be at risk of taking on a research project that can’t be satisfactorily completed.

Developing good qualitative research questions

All researchers use research questions to define their parameters, keep their study on track and maintain focus on the research topic. This is especially important with qualitative questions, where there may be exploratory or inductive methods in use that introduce researchers to new and interesting areas of inquiry. Here are some tips for writing good qualitative research questions.

1. Keep it specific

Broader research questions are difficult to act on. They may also be open to interpretation, or leave some parameters undefined.

Strong example: How do Baby Boomers in the USA feel about their gender identity?

Weak example: Do people feel different about gender now?

2. Be original

Look for research questions that haven’t been widely addressed by others already.

Strong example: What are the effects of video calling on women’s experiences of work?

Weak example: Are women given less respect than men at work?

3. Make it research-worthy

Don’t ask a question that can be answered with a ‘yes’ or ‘no’, or with a quick Google search.

Strong example: What do people like and dislike about living in a highly multi-lingual country?

Weak example: What languages are spoken in India?

4. Focus your question

Don’t roll multiple topics or questions into one. Qualitative data may involve multiple topics, but your qualitative questions should be focused.

Strong example: What is the experience of disabled children and their families when using social services?

Weak example: How can we improve social services for children affected by poverty and disability?

4. Focus on your own discipline, not someone else’s

Avoid asking questions that are for the politicians, police or others to address.

Strong example: What does it feel like to be the victim of a hate crime?

Weak example: How can hate crimes be prevented?

5. Ask something researchable

Big questions, questions about hypothetical events or questions that would require vastly more resources than you have access to are not useful starting points for qualitative studies. Qualitative words or subjective ideas that lack definition are also not helpful.

Strong example: How do perceptions of physical beauty vary between today’s youth and their parents’ generation?

Weak example: Which country has the most beautiful people in it?

Related resources

Qualitative research design 12 min read, primary vs secondary research 14 min read, business research methods 12 min read, qualitative research interviews 11 min read, market intelligence 10 min read, marketing insights 11 min read, ethnographic research 11 min read, request demo.

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Methodology

• Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

Table of contents

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

• Surveys :  List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
• Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
• Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

• Interviews : Asking open-ended questions verbally to respondents.
• Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
• Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
• Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

• Use quantitative research if you want to confirm or test something (a theory or hypothesis )
• Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores ( means )
• The number of times a particular answer was given
• The correlation or causation between two or more variables
• The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

• Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
• Thematic analysis : Closely examining the data to identify the main themes and patterns
• Discourse analysis : Studying how communication works in social contexts

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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