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| Criterion |  Operations Visual Management |  Growth A/B Testing |  Growth Funnel Analysis |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | With high tempo and many parallel topics, the method makes status, deviations, and priorities visible at a glance. It reduces search effort and prevents what matters from getting lost in daily work. | 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 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 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. |
Complexitydifferent | Low | High | Medium | Medium |
Timedifferent | Ongoing | 1-4 Wochen | 1-3 h | 1-5 Tage |
Participantsdifferent | 1-20 | 1-6 | 1-5 | Nutzertraffic |
Formatdifferent | Workshop + async | Async | Async | Async |
Outputdifferent | Visual Board, Status Indicators, Exception Cues | Experiment results, Decision log, Learning summary | Funnel report, Drop-off analysis, Optimization hypotheses | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | SignalsOperationsVisual management | ExperimentsGrowthAnalyticsValidation | AnalyticsConversionGrowth | ValidationExperimentsDemandDiscovery |