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| Criterion |  Decision Making Decision Matrix |  Product Discovery Fake Door Test |  Growth A/B Testing |  Product Strategy ICE Scoring |
|---|---|---|---|---|
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 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. | When ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list. |
Complexitydifferent | Medium | Medium | High | Low |
Timedifferent | 45-90 min | 1-5 Tage | 1-4 Wochen | 30-60 min |
Participantsdifferent | 2-8 | Nutzertraffic | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Async | Async | Workshop + async |
Outputdifferent | Decision Matrix, Scoring Rationale, Selected Option | Click Data, Interest Signal, Learning Decision | Experiment results, Decision log, Learning summary | ICE Table, Top Idea List |
Tagsno overlap | DecisionCriteriaScoringTradeoffs | ValidationExperimentsDemandDiscovery | ExperimentsGrowthAnalyticsValidation | PrioritizationScoringGrowthDecision |