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| Criterion |  Product Strategy DIBB |  Product Discovery Fake Door Test |  Product Discovery Experiment Canvas |  Decision Making Assumption Surfacing |
|---|---|---|---|---|
Purposedifferent | 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. | 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. | Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it. |
Complexitydifferent | Low | Medium | Low | Low |
Timedifferent | 1-2 h | 1-5 Tage | 30-60 min | 45-90 min |
Participantsdifferent | 2-8 | Nutzertraffic | 1-5 | 2-8 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop + async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Click Data, Interest Signal, Learning Decision | Completed Experiment Canvas, Success Metric | Assumption List, Critical Assumptions, Learning Plan |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | ValidationExperimentsDemandDiscovery | ExperimentsValidationDiscoveryHypothesis | AssumptionsRiskDecisionDiscovery |