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| Criterion |  Growth Funnel Analysis |  Product Strategy KPI Tree |  Product Discovery Fake Door Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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. | 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 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 | Medium | Medium | High |
Timedifferent | 1-3 h | 90-180 min initial, dann laufend | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 1-5 | 3-8 | Nutzertraffic | 1-6 |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | KPI Tree, Owner List | Click Data, Interest Signal, Learning Decision | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | MetricsStrategyAlignmentMeasurement | ValidationExperimentsDemandDiscovery | ExperimentsGrowthAnalyticsValidation |