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| Criterion |  Decision Making Delphi Method |  Growth A/B Testing |  Product Discovery Fake Door Test |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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 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. | 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. |
Complexitydifferent | High | High | Medium | Low |
Timedifferent | 1-4 Wochen | 1-4 Wochen | 1-5 Tage | 1-5 Tage |
Participantsdifferent | 6-30 Experten | 1-6 | Nutzertraffic | Nutzertraffic |
Formatsame | Async | Async | Async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Experiment results, Decision log, Learning summary | Click Data, Interest Signal, Learning Decision | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ForecastingExpertsDecisionStrategy | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandDiscovery | ValidationExperimentsDemandGrowth |