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| Criterion |  UX Research Affinity Diagramming |  Innovation Design Thinking |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
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. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | Low | High | Medium | High |
Timedifferent | 45–90 min | 1 Tag bis mehrere Wochen | 45-60 min | 1-4 Wochen |
Participantsdifferent | 3-10 | 4-10 | 2-8 | 1-6 |
Formatdifferent | Workshop | Workshop | Workshop + async | Async |
Outputdifferent | Theme clusters, Insight statements, Opportunity areas | Problem Statement, Prototype, Test Learnings | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | SynthesisQualitativeRoot cause | InnovationPrototypeResearch | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |