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| Criterion |  Growth Funnel Analysis |  Operations Root Cause Tree Analysis |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
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. | For a problem with several suspected causes, the method builds a causal structure instead of a mere list. It makes visible how causes connect and where the strongest points of leverage lie. | 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 only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | Medium | Medium | High | Low |
Timedifferent | 1-3 h | 1-3 h | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 1-5 | 2-8 | 1-6 | Nutzertraffic |
Formatdifferent | Async | Workshop | Async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Cause Tree, Evidence Notes, Countermeasures | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | AnalyticsConversionGrowth | Root causeTreeIncidentQuality | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |