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| Criterion |  Decision Making Delphi Method |  Growth A/B Testing |  Product Discovery MVP Test Matrix |  Product Discovery Fake Door 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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. | 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 | High | Medium | Medium |
Timedifferent | 1-4 Wochen | 1-4 Wochen | 45-75 min | 1-5 Tage |
Participantsdifferent | 6-30 Experten | 1-6 | 2-8 | Nutzertraffic |
Formatdifferent | Async | Async | Workshop | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Experiment results, Decision log, Learning summary | Test Matrix, Test Plan | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ForecastingExpertsDecisionStrategy | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryOptions | ValidationExperimentsDemandDiscovery |