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| Criterion |  Growth A/B Testing |  Growth Funnel Analysis |  Operations MORT 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 safety-relevant event or a system with high protection requirements, the method examines where controls failed. It exposes both technical and organizational gaps. |
Complexitydifferent | High | Medium | High |
Timedifferent | 1-4 Wochen | 1-3 h | Mehrere Tage bis Wochen |
Participantsdifferent | 1-6 | 1-5 | 2-6 |
Formatdifferent | Async | Async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Funnel report, Drop-off analysis, Optimization hypotheses | MORT Worksheets, Findings per Branch, Corrective Actions, Systemic Recommendations |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | AnalyticsConversionGrowth | Root causeSafetySystemicIncident |
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