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| Criterion |  Growth A/B Testing |  Agile Example Mapping |  Product Discovery Smoke Test |  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 a story carries business rules and exceptions, it brings clarity before implementation. It makes examples, open questions, and boundaries visible enough that the logic becomes jointly sound. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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 | Low | Low | Medium |
Timedifferent | 1-4 Wochen | 30-60 min | 1-5 Tage | 1-5 Tage |
Participantsdifferent | 1-6 | 3-7 | Nutzertraffic | Nutzertraffic |
Formatdifferent | Async | Workshop | Async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Example Map, Acceptance Criteria, Open Questions | Interest Metrics, Conversion Signal, Learning Note | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Behavior-Driven DevelopmentRequirementsExamplesRefinement | ValidationExperimentsDemandGrowth | ValidationExperimentsDemandDiscovery |