Qualitative research is a systematic approach to understanding human experience, meaning, and social phenomena through non-numerical data — primarily text, speech, and observation. Rather than measuring how many people hold a view, it explores what those views mean, why people hold them, and how they relate to context. The main methods include interviews, focus groups, ethnography, case studies, and document analysis.
What is qualitative research?
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Qualitative research investigates questions about meaning, experience, and context that numbers alone cannot answer. While quantitative research asks "how many?" or "how much?", qualitative research asks "why?", "how?", and "what does this mean to the people involved?"
The data in qualitative research is primarily textual: interview transcripts, field notes, documents, open-ended survey responses, social media posts, policy submissions. The analysis involves finding patterns of meaning in that text rather than calculating statistics.
Qualitative research is used in academic disciplines including sociology, psychology, education, health sciences, political science, and management, as well as in applied contexts including market research, UX research, policy analysis, HR, and strategy consulting.
How does qualitative research differ from quantitative research?
| Qualitative | Quantitative | |
|---|---|---|
| Core question | Why / how / what does it mean | How many / how much / to what degree |
| Data type | Text, speech, observation, images | Numbers, ratings, counts |
| Sample size | Small, purposive | Large, representative |
| Analysis | Interpretation, pattern-finding | Statistical analysis |
| Goal | Understanding | Measurement |
| Strengths | Depth, context, discovery | Generalisability, precision |
| Limitations | Not generalisable to populations | Misses meaning and context |
The two approaches are not opposites. Many strong research designs use both — qualitative methods to understand the phenomenon, quantitative methods to measure its extent. Alan Bryman's analysis of 232 mixed-methods studies found that the most common rationale for combining methods was that qualitative research provided explanations for quantitative findings that the numbers alone could not supply.
What are the main qualitative research methods?
Interviews
One-to-one conversations between a researcher and a participant, structured around a topic guide. Interviews are the most widely used qualitative data collection method because they allow for depth, follow-up questions, and the exploration of individual experience.
Interviews can be semi-structured (a guide of topics, but flexible in delivery) or unstructured (open conversation around a broad question). For tips on running effective interviews, see how to conduct effective business interviews.
Focus groups
Group discussions with typically six to ten participants, facilitated by a researcher. Focus groups are useful for understanding shared views and social norms, for exploring how people negotiate meaning in a group context, and for generating a wide range of perspectives efficiently.
The dynamic between participants — agreement, disagreement, elaboration — produces data that one-on-one interviews cannot. For a detailed comparison, see focus groups vs individual interviews.
Ethnography and observation
The researcher spends extended time in the field, observing behaviour and participating in the context they are studying. Ethnography is suited to understanding practices that people cannot easily articulate in an interview — what they do rather than what they say they do.
Observation can be participant (the researcher takes part in the setting) or non-participant (the researcher observes without participating). Barbara Kawulich's widely cited framework for participant observation describes the range of researcher roles from complete observer to complete participant.
Case study research
In-depth investigation of one or a small number of cases — an organisation, a policy, a project, an event. Case study research typically uses multiple data sources (interviews, documents, observations) to build a rich picture of the case. It is suited to understanding complex phenomena in their real-world context.
Document and text analysis
Systematic analysis of existing texts: policy documents, corporate reports, social media, news coverage, historical records. Document analysis is non-intrusive (it does not require access to participants) and suits questions about institutional behaviour, public discourse, and historical change.
For a full overview of qualitative research methods and when to use each, see qualitative research methods: 5 main approaches explained.
When should you use qualitative research?
Qualitative research is the right choice when:
- You are exploring a new or poorly understood phenomenon. If you do not yet know what the relevant variables are, quantitative measurement is premature.
- You need to understand why people behave as they do, not just that they do.
- Your research question concerns meaning, experience, or process.
- Your target group is small, specialist, or hard to reach — where a statistically representative sample is impossible.
- You want to test whether your assumptions are correct before investing in a large quantitative study.
Qualitative research is less suited when you need to generalise to a large population with statistical precision, or when your research question requires controlled comparison between groups.
What is purposive sampling in qualitative research?
Unlike quantitative research, qualitative research does not aim for random or representative samples. Instead, researchers use purposive sampling: selecting participants who have the knowledge, experience, or perspective needed to illuminate the research question.
If you are studying the experience of early-career doctors in rural hospitals, you want exactly those people — not a random sample of all doctors. Qualitative research seeks theoretical richness, not statistical representativeness.
Sample sizes in qualitative research are typically small: 10-30 interviews is common in academic research. The right number depends on when you reach saturation — the point at which additional interviews are not producing new themes. For guidance on sample size, see qualitative research sample size.
What are the main approaches to qualitative data analysis?
Once data is collected, it needs to be analysed. The most widely used analytical approaches are:
Thematic analysis. Identifying patterns of meaning (themes) across the dataset. Braun & Clarke's thematic analysis framework is the most widely cited approach. See what is thematic analysis? for a full explanation.
Grounded theory. Building a theory inductively from the data, through successive rounds of coding and theoretical development. Suited to research that aims to develop new theoretical explanations rather than apply existing ones. See grounded theory methodology: a practical guide.
Interpretive phenomenological analysis (IPA). A detailed examination of lived experience, typically with very small samples (3-8 participants). Suited to psychological and health research. See interpretive phenomenological analysis.
Content analysis. Counting and categorising the content of text. More systematic and less interpretive than thematic analysis; bridges qualitative and quantitative approaches. For a direct comparison, see content analysis vs thematic analysis.
Narrative analysis. Examining how people construct stories about their experience. Suited to research on identity, biography, and meaning-making.
What are the strengths and limitations of qualitative research?
Strengths:
- Depth. A 45-minute interview produces more nuanced understanding of one person's perspective than 100 survey responses from that same person.
- Contextual sensitivity. Qualitative research captures how meaning is shaped by context — organisational culture, historical circumstance, social relationships.
- Discovery. Qualitative research finds things you were not looking for. The unexpected finding is a feature, not a problem.
- Appropriate for sensitive topics. Participants often share more in a conversation than in a structured survey.
Limitations:
- Not generalisable. Findings from 20 interviews cannot be claimed to represent all members of a population.
- Time-intensive. Collection and analysis are both demanding. AI tools like Skimle substantially reduce the analysis burden, but qualitative research still requires more researcher investment per data point than quantitative approaches.
- Interpretive subjectivity. Different researchers may analyse the same data differently. Rigour requires transparency about how analysis was conducted, not an absence of interpretation.
For academic researchers, the interpretive nature of qualitative research is a methodological feature, not a weakness — it is what allows qualitative research to capture complexity that quantitative methods miss.
Frequently asked questions
Is qualitative research scientific?
Qualitative research is systematic and rigorous, but it operates under different standards than natural-science empiricism. It does not aim for the replication of results across laboratories; it aims for credibility, transferability, and transparency of interpretation. Many of the most important findings in social science, psychology, health research, and organisational studies come from qualitative research.
Can qualitative research be used in business?
Widely. Customer discovery interviews, user research, expert interviews for due diligence, focus groups for brand strategy, exit interview analysis, open-ended employee surveys — these are all qualitative research applied in business contexts. For a practical guide to qualitative research in business settings, see qualitative research for consultants.
How long does qualitative research take?
Data collection (interviewing) and transcription take roughly four to six hours per interview, including scheduling, conducting, and transcribing. Analysis of a 20-interview dataset typically takes two to four weeks manually. With AI-assisted tools like Skimle, the coding and initial theme-identification step shrinks to hours, though researcher review and write-up remain significant time investments.
What is the difference between qualitative and mixed methods research?
Mixed methods research combines qualitative and quantitative data collection in the same study. The qualitative component provides depth and context; the quantitative component provides breadth and generalisability. For a full explanation, see mixed methods research.
Want to analyse your qualitative data more efficiently? Try Skimle for free — AI-assisted qualitative analysis with full traceability from findings to source data.
Related reading:
- Qualitative research methods: 5 main approaches explained
- What is qualitative data?
- Qualitative research sample size: how many interviews do you need?
About the authors
Henri Schildt is a Professor of Strategy at Aalto University School of Business and co-founder of Skimle. He has published over a dozen peer-reviewed articles using qualitative methods, including work in Academy of Management Journal, Organisation Science, and Strategic Management Journal. His research focuses on organisational strategy, innovation, and qualitative methodology. Google Scholar profile
Olli Salo is a former Partner at McKinsey & Company where he spent 18 years helping clients understand the markets and themselves, develop winning strategies and improve their operating models. He has done over 1000 client interviews and published over 10 articles on McKinsey.com and beyond. LinkedIn profile
Sources
- Integrating quantitative and qualitative research: how is it done? — Bryman, Qualitative Research (2006)
- Participant Observation as a Data Collection Method — Kawulich, Forum: Qualitative Social Research (2005)
- Using thematic analysis in psychology — Braun & Clarke, Qualitative Research in Psychology (2006)
