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| Criterion |  Product Discovery Fake Door Test |  Decision Making Force Field Analysis |  Growth A/B Testing |
|---|---|---|---|
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 two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | Medium | Low | High |
Timedifferent | 1-5 Tage | 45-90 min | 1-4 Wochen |
Participantsdifferent | Nutzertraffic | 3-12 | 1-6 |
Formatdifferent | Async | Workshop | Async |
Outputdifferent | Click Data, Interest Signal, Learning Decision | Force Field Map, Change Levers, Risk Notes | Experiment results, Decision log, Learning summary |
Tagsno overlap | ValidationExperimentsDemandDiscovery | ChangeDecisionStrategy | ExperimentsGrowthAnalyticsValidation |
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