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| Criterion |  Growth A/B Testing |  UX Research HEART Framework |  Growth Pirate Metrics AARRR |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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. | 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | High | Medium | Medium | Low |
Timedifferent | 1-4 Wochen | 120 min initial, dann laufend | 1-2 h Setup, laufend | 30-60 min |
Participantsdifferent | 1-6 | 3-6 | 2-8 | 1-5 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | HEART-GSM Table, Dashboard | AARRR funnel, Metric baseline, Experiment backlog | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | MetricsUX researchMeasurementSatisfaction | GrowthMetricsExperiments | ExperimentsValidationDiscoveryHypothesis |