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| Criterion |  Decision Making Delphi Method |  Growth Pirate Metrics AARRR |  Product Strategy DIBB |  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. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | 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 | Low | High |
Timedifferent | 1-4 Wochen | 1-2 h Setup, laufend | 1-2 h | 1-4 Wochen |
Participantsdifferent | 6-30 Experten | 2-8 | 2-8 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | AARRR funnel, Metric baseline, Experiment backlog | DIBB document, Belief list, Bet list, Learning report | Experiment results, Decision log, Learning summary |
Tagsno overlap | ForecastingExpertsDecisionStrategy | GrowthMetricsExperiments | StrategyDecisionAssumptionsHypothesis | ExperimentsGrowthAnalyticsValidation |