Affinity mapping

A workshop technique for sorting many qualitative inputs into emergent groups by similarity — the analog ancestor of automated theme clustering.

Affinity mapping is the technique most product intelligence software is automating. The method: write each customer quote, observation, or insight on a sticky note; spread them across a wall; cluster the notes that feel related; label each cluster once it stabilizes. The clusters that emerge are the themes — the patterns that weren't visible when each note was read in isolation.

The method came out of design research and is still the standard way to synthesize interview transcripts in a workshop. Its strength is that it surfaces patterns the analyst didn't go in looking for; the structure emerges from the data rather than being imposed on it. Its weakness is scale — a workshop can handle a few hundred notes; a B2B company's monthly feedback flow is two orders of magnitude larger.

The shape of the work doesn't change when an LLM does the clustering instead of a wall full of stickies. The signals still need to be grouped by what they're actually about, not by what they sound like; the clusters still need to be named honestly; the human still has to decide which groupings deserve to become roadmap commitments. The tool changes the throughput, not the judgement.