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| Criterion |  Growth A/B Testing |  Product Discovery Fake Door Test |  Product Strategy KPI Tree |
|---|---|---|---|
Purposedifferent | 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. | 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. |
Complexitydifferent | High | Medium | Medium |
Timedifferent | 1-4 Wochen | 1-5 Tage | 90-180 min initial, dann laufend |
Participantsdifferent | 1-6 | Nutzertraffic | 3-8 |
Formatdifferent | Async | Async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Click Data, Interest Signal, Learning Decision | KPI Tree, Owner List |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandDiscovery | MetricsStrategyAlignmentMeasurement |
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