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| Criterion |  Product Strategy ICE Scoring |  Growth Growth Experiment |  Product Strategy RICE Scoring |  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 many initiatives compete for the same resources, it brings reach, impact, confidence, and effort into one shared ranking. It makes prioritization economically connectable. | 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 | 60-90 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 1-6 | 2-10 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | ICE Table, Top Idea List | Experiment card, Result summary, Next bet | RICE Scores, Ranked List, Assumption Log | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationScoringGrowthDecision | MarketingGrowthExperimentsLearning | PrioritizationScoringRoadmapTradeoffs | ExperimentsGrowthAnalyticsValidation |