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| Criterion |  Growth A/B Testing |  Growth Growth Experiment |  Operations Root Cause Analysis |  Operations Root Cause Tree 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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | 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. | 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. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 1-2 Wochen | 1-4 h | 1-3 h |
Participantsdifferent | 1-6 | 1-6 | 3-8 | 2-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Experiment card, Result summary, Next bet | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Cause Tree, Evidence Notes, Countermeasures |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | MarketingGrowthExperimentsLearning | Root causeProblem solvingQualityIncident | Root causeTreeIncidentQuality |