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| Criterion |  UX Research HEART Framework |  Growth Pirate Metrics AARRR |  UX Research Diary Study |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 experiences build up over days or weeks and a single session cannot capture them, Diary Study records the course of everyday life. Recurring triggers, moods, and habits become visible this way, beyond the sharpness of memory. | 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 | Medium | Medium | Medium | High |
Timedifferent | 120 min initial, dann laufend | 1-2 h Setup, laufend | 1-4 Wochen | 1-4 Wochen |
Participantsdifferent | 3-6 | 2-8 | 5-20 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | HEART-GSM Table, Dashboard | AARRR funnel, Metric baseline, Experiment backlog | Diary Entries, Longitudinal Patterns, Experience Timeline | Experiment results, Decision log, Learning summary |
Tagsno overlap | MetricsUX researchMeasurementSatisfaction | GrowthMetricsExperiments | UX researchTrackingBehavior | ExperimentsGrowthAnalyticsValidation |