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| Criterion |  Growth A/B Testing |  Operations Root Cause Tree Analysis |  Product Discovery Smoke Test |  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. | 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 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 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 | Low | Medium |
Timedifferent | 1-4 Wochen | 1-3 h | 1-5 Tage | 1-4 h |
Participantsdifferent | 1-6 | 2-8 | Nutzertraffic | 3-8 |
Formatdifferent | Async | Workshop | Async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Cause Tree, Evidence Notes, Countermeasures | Interest Metrics, Conversion Signal, Learning Note | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Root causeTreeIncidentQuality | ValidationExperimentsDemandGrowth | Root causeProblem solvingQualityIncident |