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| Criterion |  Decision Making Delphi Method |  Product Discovery Smoke Test |  Product Discovery Fake Door Test |  Growth A/B Testing |
|---|---|---|---|---|
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 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. | 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. |
Complexitydifferent | High | Low | Medium | High |
Timedifferent | 1-4 Wochen | 1-5 Tage | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 6-30 Experten | Nutzertraffic | Nutzertraffic | 1-6 |
Formatsame | Async | Async | Async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Interest Metrics, Conversion Signal, Learning Note | Click Data, Interest Signal, Learning Decision | Experiment results, Decision log, Learning summary |
Tagsno overlap | ForecastingExpertsDecisionStrategy | ValidationExperimentsDemandGrowth | ValidationExperimentsDemandDiscovery | ExperimentsGrowthAnalyticsValidation |