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| Criterion |  UX Research Affinity Diagramming |  Innovation Design Thinking |  Product Strategy DIBB |
|---|---|---|---|
Purposedifferent | When research notes, feedback, or observations sit unconnected side by side, affinity diagramming sorts the raw material into solid themes. Many individual points turn into patterns that make decisions and opportunities clearer. | For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. |
Complexitydifferent | Low | High | Low |
Timedifferent | 45–90 min | 1 Tag bis mehrere Wochen | 1-2 h |
Participantsdifferent | 3-10 | 4-10 | 2-8 |
Formatdifferent | Workshop | Workshop | Workshop + async |
Outputdifferent | Theme clusters, Insight statements, Opportunity areas | Problem Statement, Prototype, Test Learnings | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | SynthesisQualitativeRoot cause | InnovationPrototypeResearch | StrategyDecisionAssumptionsHypothesis |
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