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| Criterion |  Growth A/B Testing |  UX Research HEART Framework |  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. | Helps clarify observations, needs, and patterns in concrete terms. It groups observations into patterns, questions, and decisions. The result is captured as a HEART-GSM table and dashboard. | 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 | Medium | Low | Medium |
Timedifferent | 1-4 Wochen | 120 min initial, dann laufend | 1-5 Tage | 1-5 Tage |
Participantsdifferent | 1-6 | 3-6 | Nutzertraffic | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | HEART-GSM Table, Dashboard | Interest Metrics, Conversion Signal, Learning Note | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | MetricsUX researchMeasurementSatisfaction | ValidationExperimentsDemandGrowth | ValidationExperimentsDemandDiscovery |