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| Criterion |  Product Strategy ICE Scoring |  Growth Growth Experiment |  Decision Making Decision Matrix |  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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | 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 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 | Medium | High |
Timedifferent | 30-60 min | 1-2 Wochen | 45-90 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 1-6 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | ICE Table, Top Idea List | Experiment card, Result summary, Next bet | Decision Matrix, Scoring Rationale, Selected Option | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationScoringGrowthDecision | MarketingGrowthExperimentsLearning | DecisionCriteriaScoringTradeoffs | ExperimentsGrowthAnalyticsValidation |