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| Criterion |  Growth Funnel Analysis |  Operations Root Cause Analysis |  Product Discovery Smoke 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 a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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 | Low | High |
Timedifferent | 1-3 h | 1-4 h | 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 | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | Root causeProblem solvingQualityIncident | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |