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| Criterion |  Growth A/B Testing |  Product Discovery Assumption Mapping |  Domain Modeling EventStorming |  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. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | When a domain consists of many events, rules, and states, it creates a shared modeling space for the team. It bundles language, flows, and boundaries before domain knowledge fragments into siloed views. | 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 | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 45-60 min | 2-8 h | 1-5 Tage |
Participantsdifferent | 1-6 | 2-8 | 5-12 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Assumption map, Test backlog, Risk ranking | Event Timeline, Ubiquitous Language, Boundaries, Open Questions | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | AssumptionsRiskExperimentsValidation | Domain-Driven DesignEventsDiscoveryWorkshop | ValidationExperimentsDemandDiscovery |