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| Criterion |  Decision Making Delphi Method |  Growth A/B Testing |  Product Discovery Concierge MVP |  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 an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. | 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 | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 6-30 Experten | 1-6 | 3-10 Kunden | Nutzertraffic |
Formatdifferent | Async | Async | Workshop + async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Experiment results, Decision log, Learning summary | Concierge Learnings, Service Blueprint, MVP Risks | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ForecastingExpertsDecisionStrategy | ExperimentsGrowthAnalyticsValidation | MVPValidationServiceDiscovery | ValidationExperimentsDemandDiscovery |