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| Criterion |  Product Strategy ICE Scoring |  Decision Making Decision Matrix |  Product Discovery Experiment Canvas |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | 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 | Medium | Low | High |
Timedifferent | 30-60 min | 45-90 min | 30-60 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 2-8 | 1-5 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | ICE Table, Top Idea List | Decision Matrix, Scoring Rationale, Selected Option | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationScoringGrowthDecision | DecisionCriteriaScoringTradeoffs | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |