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| Criterion |  Growth A/B Testing |  UX Research HEART Framework |  Product Discovery Assumption Mapping |  Growth Pirate Metrics AARRR |
|---|---|---|---|---|
Purposedifferent | 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. | Helps clarify observations, needs, and patterns in concrete terms. It groups observations into patterns, questions, and decisions. The result is captured as a HEART-GSM table and dashboard. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 120 min initial, dann laufend | 45-60 min | 1-2 h Setup, laufend |
Participantsdifferent | 1-6 | 3-6 | 2-8 | 2-8 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | HEART-GSM Table, Dashboard | Assumption map, Test backlog, Risk ranking | AARRR funnel, Metric baseline, Experiment backlog |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | MetricsUX researchMeasurementSatisfaction | AssumptionsRiskExperimentsValidation | GrowthMetricsExperiments |