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Types of qualitative research designs

Last updated

20 February 2023


Dovetail Editorial Team

Reviewed by

Jean Kaluza

You can use different research types to meet your study's specific goals. Qualitative research methods gather in-depth insights into user motivations and their experiences.

Researchers often conduct these studies to gain a detailed understanding of a particular topic through a small, focused sample. Qualitative research methods delve into understanding why something is happening in a larger quantitative study. 

To determine whether qualitative research is the best choice for your study, let’s look at the different types of qualitative research design.

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What are qualitative research designs?

Qualitative research designs are research methods that collect and analyze non-numerical data. The research uncovers why or how a particular behavior or occurrence takes place. The information is usually subjective and in a written format instead of numerical.

Researchers may use interviews, focus groups, case studies, journaling, and open-ended questions to gather in-depth information. Qualitative research designs can determine users' concepts, develop a hypothesis, or add context to data from a quantitative study.

Characteristics of qualitative research design

Most often, qualitative data answers how or why something occurs. Certain characteristics are usually present in all qualitative research designs to ensure accurate data. 

The most common characteristics of qualitative research design include the following:

Natural environment

It’s best to collect qualitative research as close to the subject’s original environment as possible to encourage natural behavior and accurate insights.

Empathy is key

Qualitative researchers collect the best data when they’re in sync with their users’ concerns and motivations. They can play into natural human psychology by combining open-ended questioning and subtle cues.

They may mimic body language, adopt the users’ terminology, and use pauses or trailing sentences to encourage their participants to fill in the blanks. The more empathic the interviewer, the purer the data.

Participant selection

Qualitative research depends on the meaning obtained from participants instead of the meaning conveyed in similar research or studies. To increase research accuracy, you choose participants randomly from carefully chosen groups of potential participants.

Different research methods or multiple data sources

To gain in-depth knowledge, qualitative research designs often rely on multiple research methods within the same group. 

Emergent design

Qualitative research constantly evolves, meaning the initial study plan might change after you collect data. This evolution might result in changes in research methods or the introduction of a new research problem.

Inductive reasoning

Since qualitative research seeks in-depth meaning, you need complex reasoning to get the right results. Qualitative researchers build categories, patterns, and themes from separate data sets to form a complete conclusion.

Interpretive data

Once you collect the data, you need to read between the lines rather than just noting what your participant said. Qualitative research is unique as we can attach actions to feedback. 

If a user says they love the look of your design but haven’t completed any tasks, it’s up to you to interpret this as a failed test, even with their positive sentiments. 

Holistic account

To paint a large picture of an issue and potential solutions, a qualitative researcher works to develop a complex description of the research problem. You can avoid a narrow cause-and-effect perspective by describing the problem’s wider perspectives. 

When to use qualitative research design

Qualitative research aims to get a detailed understanding of a particular topic. To accomplish this, you’ll typically use small focus groups to gather in-depth data from varied perspectives. 

This approach is only effective for some types of study. For instance, a qualitative approach wouldn’t work for a study that seeks to understand a statistically relevant finding.

When determining if a qualitative research design is appropriate, remember the goal of qualitative research is understanding the “why.” 

Qualitative research design gathers in-depth information that stands on its own. It can also answer the “why” of a quantitative study or be a precursor to forming a hypothesis. 

You can use qualitative research in these situations:

  • Developing a hypothesis for testing in a quantitative study

  • Identifying customer needs

  • Developing a new feature

  • Adding context to the results of a quantitative study

  • Understanding the motivations, values, and pain points that guide behavior

Qualitative and quantitative research designs gather data, but that's where the similarities end. Consider the difference between quality and quantity. Both are useful in different ways.

Qualitative research gathers in-depth information to answer how or why. It uses subjective data from detailed interviews, observations, and open-ended questions. Most often, qualitative data is thoughts, experiences, and concepts.

In contrast, quantitative research designs gather large amounts of objective data that you can quantify mathematically. You typically express quantitative data in numbers or graphs, and you use it to test or confirm hypotheses.

Types of qualitative research designs

Qualitative research designs generally have the same goals. However, there are various ways to achieve these goals. Researchers may use one or more of these approaches in qualitative research.

Historical study

This is where you use extensive information about people and events in the past to draw conclusions about the present and future.


Phenomenology investigates a phenomenon, activity, or event using data from participants' perspectives. Often, researchers use a combination of methods.

Grounded theory

Grounded theory uses interviews and existing data to build a theory inductively.


Researchers immerse themselves in the target participant's environments to understand goals, cultures, challenges, and themes with ethnography.

Case study

A case study is where you use multiple data sources to examine a person, group, community, or institution. Participants must share a connection to the research question you’re studying.

Advantages and disadvantages of qualitative research

All qualitative research design types share the common goal of obtaining in-depth information. Achieving this goal generally requires extensive data collection methods that can be time-consuming. As such, qualitative research has advantages and disadvantages. 


Natural settings

Since you can collect data closer to an authentic environment, it offers more accurate results.  

The ability to paint a picture with data

Quantitative studies don't always reveal the full picture. With multiple data collection methods, you can expose the motivations and reasons behind data.


Analysis processes aren't set in stone, so you can adapt the process as ideas or patterns emerge.

Generation of new ideas

Using open-ended responses can uncover new opportunities or solutions that weren't part of your original research plan.

Small sample sizes

You can generate meaningful results with small groups.


Potentially unreliable

A natural setting can be a double-edged sword. The inability to attach findings to anything statistically relevant can make data more difficult to quantify. 


Since the researcher plays a vital role in collecting and interpreting data, qualitative research is subject to the researcher's skills. For example, they may miss a cue that changes some of the context of the quotes they collected.


You generally collect qualitative data through manual processes like extensive interviews, open-ended questions, and case studies.

Qualitative research designs allow researchers to provide an in-depth analysis of why specific behavior or events occur. It can offer fresh insights, generate new ideas, or add context to statistics from quantitative studies. Depending on your needs, qualitative data might be a great way to gain the information your organization needs to move forward.

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