Affinity Mapping
Group individual observations until themes emerge from the data instead of from the categories you brought with you.
Definition
Affinity mapping is bottom-up clustering: write each observation on its own note, group related notes, then name the groups. Naming last is the whole method, because naming first turns the exercise into sorting into expectations.
Craft convention. True because the industry converged on it. Breaking it costs familiarity, not correctness.
On this plate
Reach for this when
- After interviews, diary studies or usability sessions.
- Synthesising open-ended survey responses.
- Combining findings from several researchers.
- A team has sat through the sessions separately and holds four different summaries.
Common mistakes
- Predefined groups.
- Themes counted by notes rather than by participants.
- Disconfirming notes quietly dropped.
- Photographing the wall and never converting the groups into written findings, so the work survives only as an image.
The method
- 1
One observation per note
A note that contains two ideas will be filed under one and lose the other. Keep the participant reference on every note.
- 2
Group in silence first
Discussion during grouping produces consensus with the loudest voice rather than with the data.
- 3
Name the groups afterwards
The name has to describe what is in the group, not the category you hoped to fill.
- 4
Split anything unwieldy
A group of thirty notes is usually three themes that have not been separated yet.
- 5
Count, then look for absence
How many participants, not how many notes, support each theme. Then ask what you expected to see and did not.
Keeping it honest
Do
- Keep observations and interpretations on visibly different notes.
- Keep a group of outliers rather than forcing every note into a theme.
- Report how many participants a theme came from, not just the theme.
- Photograph the intermediate state, so the path from raw notes to conclusion can be reviewed.
Do not
- Do not start with predefined categories.
- Do not let one talkative participant's quotes dominate through sheer volume of notes.
- Do not throw away the notes that contradict the emerging story. Those are the interesting ones.
Where sessions go wrong
| Symptom | What is actually happening | Repair |
|---|---|---|
| Groups named in the first ten minutes | Sorting into expectations rather than finding structure | Cover the names until every note is placed |
| One enormous group | The label is too abstract to mean anything | Split it and force each half to justify itself |
| Notes that say the whole story | One note carries three observations and lands anywhere | One observation per note, rewritten on the spot |
| Everyone deferring to one person | The senior view is being mapped, not the data | Place notes silently for the first pass |
In practice
- i.
The group nobody wanted
The leftover pileThe notes that fit nowhere are usually treated as noise and swept up at the end. They are more often the observations that do not match the team's existing model, which makes them the most informative pile on the wall.
Commonly confused with
Close neighbours that get substituted for each other. The difference is stated first, then the condition that picks one over the other.
Research Synthesis
Research methodCoding raw data, forming themes and deriving findings that inform decisions.
Key difference
Synthesis is the whole step from raw data to findings a team can act on. Affinity mapping is one technique inside it. Clustering notes on a wall is not synthesis until the themes are interrogated and turned into findings.
Use Affinity Mapping when
- You have a pile of observations and no structure yet.
- The session is collaborative and needs a concrete activity.
- Naming last is the point, so expectations do not drive the sorting.
Use Research Synthesis when
- The question is how to get from sessions to conclusions.
- Rigour, traceability and bias are the concern.
- The output has to survive being challenged.
Local chart
RES·020 · Region IV · Grid G2
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Continue from here
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Principles behind this
The reasoning this solution is an application of.
- Confirmation BiasBIAS·009 · Cognitive bias
Related concept
Connected closely enough to change how you apply this.
- Research Notes to InsightsAI·003 · AI workflow
- Card SortingRES·005 · Research method
- Diary StudiesRES·013 · Research method
- User InterviewsRES·003 · Research method