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| Criterion |  Product Discovery Fake Door Test |  Product Strategy KPI Tree |  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. | When metrics across the organization drift apart, it arranges drivers and effects under one shared logic. It connects customer value, product logic, and decision priorities. The result is captured as a KPI tree and owner list. | 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 | Medium | Low |
Timedifferent | 1-5 Tage | 90-180 min initial, dann laufend | 1-2 h |
Participantsdifferent | Nutzertraffic | 3-8 | 2-8 |
Formatdifferent | Async | Workshop + async | Workshop + async |
Outputdifferent | Click Data, Interest Signal, Learning Decision | KPI Tree, Owner List | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ValidationExperimentsDemandDiscovery | MetricsStrategyAlignmentMeasurement | StrategyDecisionAssumptionsHypothesis |
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