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| Criterion |  Growth A/B Testing |  Growth Funnel Analysis |  Operations Root Cause Tree Analysis |  Operations Root Cause Analysis |
|---|---|---|---|---|
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 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 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. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 1-3 h | 1-3 h | 1-4 h |
Participantsdifferent | 1-6 | 1-5 | 2-8 | 3-8 |
Formatdifferent | Async | Async | Workshop | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Funnel report, Drop-off analysis, Optimization hypotheses | Cause Tree, Evidence Notes, Countermeasures | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | AnalyticsConversionGrowth | Root causeTreeIncidentQuality | Root causeProblem solvingQualityIncident |