The tools kept changing. The reason card sorting works did not. This is the thinking SortedResearch is built on.
In the 1960s a Japanese ethnographer, Jiro Kawakita, built a way of working he called the KJ Method, set out across three books between 1967 and 1986. His premise was that real understanding of a subject comes from the field itself, and not from a theory laid over the top of it.
He called this field science. The tool was plain: one idea per card, spread on a table, grouped by hand until the patterns surfaced. From there the method spread through product development, planning and quality work across Japan, and then well beyond it.
One idea per card. Card sorting groups them by affinity, the way Kawakita did by hand. Pairwise then ranks those groups by importance and satisfaction, so the biggest opportunities rise to the top.
Three ideas carry straight over from the table of cards to the software.
Open sorts hand participants a deck with no groups set in advance. The structure comes out of the data. This is Kawakita's abductive principle: let the field speak before the researcher interprets.
Kawakita's table encoded closeness as meaning. Cards that sat together belonged together. The similarity matrix and clustering dendrogram in SortedResearch are the computational form of that same idea.
Kawakita watched how the groups sat in relation to each other, beyond which card went where. The 3D view in SortedResearch makes that spatial structure legible at scale, across hundreds of participants, in seconds.
Two places SortedResearch moves past what Kawakita could do at a table.
Kawakita worked with small teams in long, immersive sessions. SortedResearch aggregates across large consumer samples, trading depth of immersion for strength of pattern. Both produce valid knowledge. They answer different questions.
Graham reads the pattern and drafts what it means. Kawakita held that the insight came through the act of grouping itself. Graham does not replace that judgment. He gives the researcher a faster place to start, and something to push against.
Card sorting answers one question: how do people group your ideas? Pairwise answers the next one. Which of those ideas matter most, and where are people underserved? It rests on two simple, well-established ideas.
Ask someone to score fifteen needs out of ten and the numbers drift. Ask them to pick between two needs at a time and the answer holds. Simple forced choices, repeated and aggregated across people, give a ranking you can trust far more than a long rating grid.
A need that matters is only an opportunity if it is poorly met. Measuring how much each need matters and how well it is served today, then reading the gap between the two, is a long-standing way to tell the real opportunities from the table stakes. That gap is what the opportunity matrix draws.
See the structure in your own category.
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