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| Criterion |  Product Discovery Assumption Mapping |  Product Discovery Experiment Canvas |  Product Strategy DIBB |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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. | 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 demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. |
Complexitydifferent | Medium | Low | Low | Medium |
Timedifferent | 45-60 min | 30-60 min | 1-2 h | 1-5 Tage |
Participantsdifferent | 2-8 | 1-5 | 2-8 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Assumption map, Test backlog, Risk ranking | Completed Experiment Canvas, Success Metric | DIBB document, Belief list, Bet list, Learning report | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | AssumptionsRiskExperimentsValidation | ExperimentsValidationDiscoveryHypothesis | StrategyDecisionAssumptionsHypothesis | ValidationExperimentsDemandDiscovery |