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| Criterion |  Growth Funnel Analysis |  Operations Fault Tree Analysis |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
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 critical top event with several possible triggers, the method logically models failure paths. It makes visible which combinations of conditions can lead to damage. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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. |
Complexitydifferent | Medium | High | Medium | High |
Timedifferent | 1-3 h | 2-6 h | 45-60 min | 1-4 Wochen |
Participantsdifferent | 1-5 | 3-8 | 2-8 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Fault Tree, Critical Paths, Cause Hypotheses, Control Actions | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | RiskRoot causeSafety | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |