What is Qualitative Data?
Qualitative data is defined as any non-mathematical information that can only be understood based on its qualities and properties.
For example, awareness of all sensations and feelings can only be described in a qualitative manner, and this information becomes qualitative data.
From a research perspective, qualitative data is collected through primary or secondary means. Primary qualitative data is any information that is gathered first hand, for example through conducting interviews, open ended questionnaires, focus groups etc.
Similarly, secondary qualitative data is any qualitative information that is already collected and you are only accessing that data, for example, reading a case study, watching an interview, listening to a recording etc.
Qualitative data vs Quantitative data
In a certain sense, one can say that everything is qualitative data, from which quantitative information arises. For example, a car ride experience is qualitative in nature, in which there are quantitative elements such as speed of the car, distance travelled etc.
So we can say that we experience the world only as qualitative, and so all experiences are qualitative in nature. Within that experience we can describe certain events with quantitative elements. For example, when we look up to see the stars, there is only the experience of looking at the stars with all the surrounding elements and sensations. Hence, a qualitative essay may be written on this experience which becomes qualitative data.
Then a specific question can be answered using quantitative means, such as, how many stars are there?
Therefore, qualitative data can carry quantitative data within it. This is how text-based data analytics are performed on qualitative data, such as the number of times a word has been repeated, occurences of numbers etc.
Key Characteristics of Qualitative Data
Let us now understand qualitative data with further depth by understanding its key characteristics:
- Descriptive, comparative and contextual
Qualitative data is descriptive, comparative and contextual in nature. For example, in a qualitative political research study, a respondent being interviewed may respond in ways such as, I prefer this political candidate over the other (comparative), I like this political candidate because of XYZ qualities (descriptive), I started following their political career since X date and I like what they said or did (contextual).
- Subjective and interpretive
All 3 characteristics described above, are all subjective and interpretive. This is because all experiences are ultimately subjective and interpretive as a whole.
For example, a car can only go at a certain quantitative and objective speed, however, that same experience can feel different to different people. So let’s say the car is going 30 miles an hour objectively, that speed may be subjectively experienced and interpreted in varying degrees of fast or slow by any 2 people.
- Flexible and open-ended collection methods
Qualitative data is always collected using methods that are not restricted by specific options, and instead kept open. During interviews for example, the questionnaire is flexible based on the answers given the respondent.
There may be a contextual scope to the questionnaire, such as a specific topic or area. For example, in a focus group, respondents may be asked for their reactions to a specific advertisement. Here, the response related to their opinion is open-ended, while the boundary of response is the advertisement.
- Generates deeper insights
Qualitative data is typically used in areas of research where there is interest in understanding a subject more deeply, especially in comparison to quantitative studies.
For example, in a quantitative consumer research survey, a simple question may be asked related to which product they like with options presented. This may be followed up with a multiple-choice option on why they like it and they may have to select one or more options as response. Such a quantitative study is always limited by the scope of options being presented and may not capture the true essence of the respondent’s preferences.
Instead, if the respondent is allowed to select the first response quantitatively, and then if the follow up is an open ended question, the researcher will get to understand the full length and breadth of a product/ feature’s popularity.
This is also why in surveys, qualitative open ended questions are often used after the initial quantitative questions to reduce limitations in quality of response capture.
Types of Qualitative Data Collection Methods with Examples
There are several qualitative data collection methods, all of which beat the characteristics described above.
Here are the key types of qualitative data collection methods:
- Interviews
Interviews can be done one-on-one or in a group to gather perspectives from people. This involves an interviewer, which may be the researcher or a hired skillful person, the topic/ subject and the participant/ interviewee.
Interviews are excellent for deep-diving a specific subject and gather multiple perspectives from different types of people ranging in demographics and viewpoints. A precursor to any interview is ensuring that the interviewee has awareness and understanding of the subject being discussed. Typically in research there are several such qualifying parameters for selecting the right people to interview.
Interviews today are conducted in-person, or remotely. The goal here is to capture respondents’ opinions rather than their immediate reactions, as is the case with focus groups.
- Focus Groups
Focus groups are used as an alternative to interviews when the goal is to gather reactions to specific stimuli such as a video, an advertisement, a specific person or event etc. This is a widely used qualitative data collection method in the field of political research and advertisement selection.
It is important to note that the prime objective of a focus group is to gather information on people’s emotional/ instinctive reactions, rather than a thought-through opinion as is the case with interviews. This is why focus groups are always conducted in a live-setting, where people’s immediate reactions to a given stimulus are seen and observed.
For example, a focus group may be shown several ads to capture their responses and the ad that produced the desired reaction is selected for launch.
Focus groups can be conducted in-person or through online conferencing technologies.
- Observations
Observations as a method of qualitative data gathering is a process by which a subject is merely observed without any direct interaction.
For example, while trying to understand the nature of a flock of birds in a certain geography, the researcher stays in an area where they won’t be a cause of interference/ distraction or disturbance to the birds and can simply observe them being themselves.
Observations as a means of understanding is also used in daily practice in the field of spiritual therapy and psychology. Here, the patient/ spiritual seeker is observed by the therapist on their reactions to themselves on certain thoughts and emotions that may be occurring, or the lack thereof.
- Documentations of all formats
Documentations as a source of qualitative data can include text, picture, audio and video. Examples of such material are documentaries, news clips, recorded therapy sessions, interviews, journals and diaries etc.
Documents are a source of secondary data, where the actual data collection has already taken place, and the researcher collects them and puts them together as citations and sources to draw or support certain conclusions. Such information may be used as the sole data for conclusions and reports or they can be supporting material apart from other types of qualitative and quantitative data.
- Artifacts and objects
In the field of anthropology and historical research, artifacts and objects are a prime source of qualitative data to understand and speculate on what may have occurred and what the past may have looked like.
Often an area of much speculation and uncertain views, such artifacts and objects require much deeper research to actually come to a reasonable conclusion. However, such conclusions over time are challenged and changed as more artifacts and objects are discovered that may support an opposite or alternate argument.
- Ethnography
Ethnography as a source of qualitative data is prevalent in the fields of journalism and cultural research. During this process, the researcher immerses themselves in the habitat and culture with full interaction to understand how they live, their varying beliefs, habits, traditions etc.
Unlike observations, where the researcher may stay distant from the subject of research, ethnography requires the researcher to be fully present and immersed in the subject’s surroundings to grab a complete understanding of their viewpoints and behaviours.
- Case studies
Case studies are a data collection method that may include secondary research in the form of published materials or primary research in the form of interviews. They are used to understand an event that has already occurred and is determined to be complete in a certain sense.
For example, when a person or company accomplished something important, a case study is often published after conducting interviews with the person/ people involved.
While case studies are typically applied on a secondary subject, it can also be applied to the self in the form of self-study in psychology or therapy.
Best practices for qualitative data collection and management
Here are the key best practices to get your research started and keep it steady throughout its lifecycle:
1. Define clear research objectives
Begin by establishing what you want to achieve with the study and what questions you aim to answer. Having clear objectives helps guide every stage of data collection, ensures the information you gather is relevant, and avoids wasting time on unrelated topics.
2. Select suitable data collection methods
Decide whether interviews, focus groups, observations, or document reviews best suit your research needs. Each method offers unique strengths: interviews provide depth, focus groups encourage interaction, and observations capture real behaviors. Choosing the right method makes the data more meaningful.
3. Develop structured protocols and tools
Prepare guides, checklists, or templates before starting fieldwork to maintain consistency. Structured tools ensure all participants are asked similar questions, reduce the influence of personal bias, and make it easier to compare responses during analysis.
4. Ensure ethical practices and consent
Always explain the purpose of the study, how the data will be used, and participants’ right to withdraw. Obtaining consent is not just about compliance but also about building trust, which leads to richer and more honest responses.
5. Record and document data carefully
Use audio or video recording, detailed field notes, and transcription tools to capture information accurately. Systematic recording reduces the risk of losing key insights and provides a reliable reference for analysis later.
6. Protect confidentiality and secure storage
Assign codes instead of names, store files in encrypted systems, and restrict access to only authorized team members. Protecting data privacy is essential for participant safety and increases the credibility of your research.
7. Apply consistent labeling and coding
Give unique identifiers to participants, sessions, and documents so data remains organized. Then apply coding schemes to responses, which helps identify themes, patterns, and connections more efficiently during analysis.
8. Create a clear data management plan
Design a plan that covers how data will be collected, stored, processed, and shared. A good plan outlines responsibilities, timelines, and tools to be used, reducing confusion and ensuring accountability throughout the project.
9. Ensure data quality through training and monitoring
Train researchers and data collectors on interviewing skills, note-taking, and ethical practices. Regular monitoring and feedback improve data reliability and reduce inconsistencies across different researchers.
10. Back up and maintain data regularly
Keep multiple secure backups of all data in case of loss or corruption. Regular maintenance of files ensures data remains accessible and usable even long after the project is complete.
