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| Criterion |  Growth A/B Testing |  Product Strategy ICE Scoring |  Product Discovery Smoke Test |  Decision Making Decision Matrix |
|---|---|---|---|---|
Purposedifferent | 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. | 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 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. |
Complexitydifferent | High | Low | Low | Medium |
Timedifferent | 1-4 Wochen | 30-60 min | 1-5 Tage | 45-90 min |
Participantsdifferent | 1-6 | 2-8 | Nutzertraffic | 2-8 |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | ICE Table, Top Idea List | Interest Metrics, Conversion Signal, Learning Note | Decision Matrix, Scoring Rationale, Selected Option |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | PrioritizationScoringGrowthDecision | ValidationExperimentsDemandGrowth | DecisionCriteriaScoringTradeoffs |