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| Criterion |  Product Discovery Opportunity Scoring |  Product Strategy ICE Scoring |  Product Discovery Opportunity Solution Tree |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When opportunities need ranking by their effect, it makes importance and satisfaction directly comparable. It separates problem, assumption, solution, and evidence. The result is captured as an opportunity-score table and top outcomes. | 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 discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure. | 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 | Medium | Low | Medium | High |
Timedifferent | 60-120 min | 30-60 min | 1-2 h Setup, laufend | 1-4 Wochen |
Participantsdifferent | 3-6 | 2-8 | 2-6 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Opportunity Score Table, Top Outcomes | ICE Table, Top Idea List | Opportunity Solution Tree, Experiment Backlog, Learning Log | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationDiscoveryOutcomesNeeds | PrioritizationScoringGrowthDecision | DiscoveryOutcomesExperimentsOpportunity | ExperimentsGrowthAnalyticsValidation |