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| Criterion |  Product Discovery Assumption Mapping |  UX Research Affinity Diagramming |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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 | Medium | Low | Low | High |
Timedifferent | 45-60 min | 45–90 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | 3-10 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop | Async | Async |
Outputdifferent | Assumption map, Test backlog, Risk ranking | Theme clusters, Insight statements, Opportunity areas | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | AssumptionsRiskExperimentsValidation | SynthesisQualitativeRoot cause | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |