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| Criterion |  Product Discovery Fake Door Test |  Decision Making Force Field Analysis |  Product Discovery Assumption Mapping |  Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | 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. | In change initiatives, supporting and restraining forces sit at the table at the same time. Force Field Analysis makes these tensions explicit and shows where change can be pushed forward by strengthening or relieving. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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. |
Complexitydifferent | Medium | Low | Medium | Low |
Timedifferent | 1-5 Tage | 45-90 min | 45-60 min | 1-2 h |
Participantsdifferent | Nutzertraffic | 3-12 | 2-8 | 2-8 |
Formatdifferent | Async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Click Data, Interest Signal, Learning Decision | Force Field Map, Change Levers, Risk Notes | Assumption map, Test backlog, Risk ranking | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ValidationExperimentsDemandDiscovery | ChangeDecisionStrategy | AssumptionsRiskExperimentsValidation | StrategyDecisionAssumptionsHypothesis |