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| Criterion |  Decision Making Delphi Method |  Product Strategy ICE Scoring |  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 ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list. | 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 | 30-60 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 6-30 Experten | 2-8 | Nutzertraffic | 1-6 |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | ICE Table, Top Idea List | Click Data, Interest Signal, Learning Decision | Experiment results, Decision log, Learning summary |
Tagsno overlap | ForecastingExpertsDecisionStrategy | PrioritizationScoringGrowthDecision | ValidationExperimentsDemandDiscovery | ExperimentsGrowthAnalyticsValidation |