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| Criterion |  Product Strategy DIBB |  Growth Pirate Metrics AARRR |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | Low | Medium | Medium | High |
Timedifferent | 1-2 h | 1-2 h Setup, laufend | 45-60 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 2-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | AARRR funnel, Metric baseline, Experiment backlog | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | GrowthMetricsExperiments | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |