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| Criterion |  Decision Making Delphi Method |  Growth Pirate Metrics AARRR |  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. | For products with complex usage paths, overall growth alone is too coarse to reveal bottlenecks. Pirate Metrics breaks the relationship with the product into consecutive stages and shows where the funnel actually leaks. | 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 | Medium | Medium | High |
Timedifferent | 1-4 Wochen | 1-2 h Setup, laufend | 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 | AARRR funnel, Metric baseline, Experiment backlog | Click Data, Interest Signal, Learning Decision | Experiment results, Decision log, Learning summary |
Tagsno overlap | ForecastingExpertsDecisionStrategy | GrowthMetricsExperiments | ValidationExperimentsDemandDiscovery | ExperimentsGrowthAnalyticsValidation |