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| Criterion |  Product Discovery Hypothesis Prioritization Canvas |  Product Strategy DIBB |  Product Strategy ICE Scoring |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | 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. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | 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 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. |
Complexitydifferent | Medium | Low | Low | Low |
Timedifferent | 60-90 min | 1-2 h | 30-60 min | 30-60 min |
Participantsdifferent | 3-8 | 2-8 | 2-8 | 1-5 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Prioritization Canvas, Hypothesis Backlog | DIBB document, Belief list, Bet list, Learning report | ICE Table, Top Idea List | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ExperimentsPrioritizationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis | PrioritizationScoringGrowthDecision | ExperimentsValidationDiscoveryHypothesis |