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| Criterion |  Decision Making Decision Matrix |  Growth Funnel Analysis |  Product Discovery Fake Door Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When several options collide with several criteria, comparison quickly becomes subjective. A Decision Matrix makes the trade-off visible and brings weighting, criteria, and options into a shared logic. | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. | 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 | Medium | Medium | High |
Timedifferent | 45-90 min | 1-3 h | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | 1-5 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Async | Async | Async |
Outputdifferent | Decision Matrix, Scoring Rationale, Selected Option | Funnel report, Drop-off analysis, Optimization hypotheses | Click Data, Interest Signal, Learning Decision | Experiment results, Decision log, Learning summary |
Tagsno overlap | DecisionCriteriaScoringTradeoffs | AnalyticsConversionGrowth | ValidationExperimentsDemandDiscovery | ExperimentsGrowthAnalyticsValidation |