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| Criterion |  Growth Funnel Analysis |  Operations Fault Tree Analysis |  Operations Causal Factor Analysis |  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. | For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events. | 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 | High | High |
Timedifferent | 1-3 h | 2-6 h | 2-6 h | 1-4 Wochen |
Participantsdifferent | 1-5 | 3-8 | 3-10 | 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 | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | RiskRoot causeSafety | CausalityIncidentRoot causeTimeline | ExperimentsGrowthAnalyticsValidation |