What is qualitative?
Qualitative refers to information that describes qualities, characteristics, or meanings rather than numbers. It’s about “what” and “why” something happens, captured through words, images, or observations instead of measurements or counts.
Let's break it down
- Data type: Text, audio, video, photos, or notes.
- Collection methods: Interviews, open‑ended surveys, focus groups, user observations, and diary studies.
- Analysis style: Looking for patterns, themes, or stories in the data, often using coding or grouping similar ideas together.
Why does it matter?
Qualitative data gives depth and context that numbers alone can’t provide. It helps you understand user motivations, discover hidden problems, and generate ideas for new features or improvements that might never show up in purely quantitative reports.
Where is it used?
- User experience (UX) research to design intuitive interfaces.
- Market research to explore consumer attitudes toward a brand.
- Software testing for usability feedback.
- AI training to label and interpret natural language.
- Business strategy sessions to capture employee insights.
Good things about it
- Provides rich, detailed insights.
- Captures emotions, opinions, and motivations.
- Flexible: can adapt questions as you learn.
- Helps generate hypotheses for later quantitative testing.
- Encourages empathy with real people’s experiences.
Not-so-good things
- Time‑consuming to collect and analyze.
- Results are harder to generalize to large populations.
- Can be subjective; different analysts may interpret the same data differently.
- Difficult to automate compared to numeric data.
- Requires skilled moderators or interviewers to avoid bias.