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| Criterion |  Product Strategy ICE Scoring |  Product Discovery Hypothesis Prioritization Canvas |  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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | 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 | 60-90 min | 30-60 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 3-8 | 1-5 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Async |
Outputdifferent | ICE Table, Top Idea List | Prioritization Canvas, Hypothesis Backlog | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationScoringGrowthDecision | ExperimentsPrioritizationDiscoveryHypothesis | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |