By the end of this lesson you can
- Prepare raw research notes for analysis.
- Group observations into themes using affinity mapping.
- Turn themes into insights that explain behaviour and suggest action.
The idea
After interviews or tests you have pages of notes. Affinity mapping is a simple way to make sense of them: write each observation on its own note, then group notes that seem related until patterns appear. It is a practical form of thematic analysis.
Observations first
Each note holds one observation: something a participant said or did, with an ID so you can trace it back ("P3: keeps a paper list of passwords"). Avoid writing interpretations at this stage. "P3 is disorganised" is a judgement; "P3 keeps passwords on paper" is an observation.
Grouping
Move notes into clusters without deciding the categories in advance. Let the groups emerge from the data. When a cluster feels coherent, give it a label that says what it means, written as a sentence: "People don't trust themselves to remember passwords" is more useful than "Passwords".
From themes to insights
A theme describes a pattern. An insight explains it and points somewhere: "People keep passwords on paper because they fear being locked out more than being hacked. Recovery feels harder than the risk." Good insights are grounded in evidence from several participants, surprising enough to be worth saying, and clear about what they imply for design.
Why it matters in real projects
Without structured analysis, teams remember the most vivid quote and forget the pattern. Affinity mapping keeps findings tied to evidence, makes analysis visible to the whole team, and turns scattered notes into a small number of insights people can act on. Doing it together also builds shared understanding, which makes findings easier to accept.
A realistic example
A team researching a hospital appointment app has notes from eight interviews: about 200 observations. They write each on a digital sticky note, tagged with the participant number.
Over an hour, clusters form. One holds notes about patients asking relatives to read letters; another about missing appointments because letters arrived late; another about phoning to confirm even after receiving a text. The team labels them, then notices the bigger pattern: patients don't trust any single channel, so they double-check everything.
The insight, "Patients phone to confirm because no single message feels official enough to rely on", leads the team to make the app the single source of truth and to say so explicitly in every reminder.
Step by step
Extract observations
Go through each session and write one observation per note, with a participant ID.
Spread them out
Put every note on a wall or digital board in no particular order.
Cluster silently
Move related notes together. Working without talking at first avoids one voice dominating.
Label clusters
Write a sentence describing what each cluster means.
Look for higher-level patterns
Group clusters into larger themes and look for relationships between them.
Write insights
For each main theme, write why it happens and what it implies, and list the supporting evidence.
Common mistakes
Mistake Writing interpretations instead of observations on notes.
Instead Record what was said or done. Interpret during clustering.
Mistake Deciding categories before grouping.
Instead Let clusters emerge from the data so you can find what you did not expect.
Mistake One-word cluster labels.
Instead Label clusters with a sentence that states the meaning.
Mistake Insights supported by one participant.
Instead Check how many participants each insight rests on and say so.
Check your understanding
Choose an answer, then check it. There is an explanation either way.
Practice exercise
Exercise · about 1 h
Affinity map from sample notes
Use notes from your own practice interviews, or write 40 realistic observations about how people choose a takeaway on a Friday night.
Steps
- Write one observation per note with a participant ID.
- Cluster them without predefined categories.
- Label each cluster with a sentence.
- Write three insights, each with its supporting evidence and a design implication.
Deliverable
A photo or export of the map and three written insights.
Self-assessment
Tick each item when it is true of your exercise. Be honest; this is for you.
4 items
Summary
- Affinity mapping groups observations into themes.
- Start with observations, not interpretations.
- Let categories emerge and label them with meaning.
- Insights explain why a pattern happens and what to do about it.
Further reading
Third-party sources, chosen for reliability. They open in a new tab.
- Affinity diagramming (opens in a new tab)Nielsen Norman Group
- How to do a thematic analysis of user interviews (opens in a new tab)Nielsen Norman Group
Your notes
Marking complete updates your course and roadmap progress.