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| Criterion |  Growth A/B Testing |  Operations Causal Factor Analysis |  Decision Making Assumption Surfacing |  Product Discovery Fake Door Test |
|---|---|---|---|---|
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 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. | Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it. | When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. |
Complexitydifferent | High | High | Low | Medium |
Timedifferent | 1-4 Wochen | 2-6 h | 45-90 min | 1-5 Tage |
Participantsdifferent | 1-6 | 3-10 | 2-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions | Assumption List, Critical Assumptions, Learning Plan | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | CausalityIncidentRoot causeTimeline | AssumptionsRiskDecisionDiscovery | ValidationExperimentsDemandDiscovery |