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| Criterion |  UX Research HEART Framework |  Growth Funnel Analysis |  Growth Pirate Metrics AARRR |  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. | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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 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 | 1-3 h | 1-2 h Setup, laufend | 1-4 Wochen |
Participantsdifferent | 3-6 | 1-5 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | HEART-GSM Table, Dashboard | Funnel report, Drop-off analysis, Optimization hypotheses | AARRR funnel, Metric baseline, Experiment backlog | Experiment results, Decision log, Learning summary |
Tagsno overlap | MetricsUX researchMeasurementSatisfaction | AnalyticsConversionGrowth | GrowthMetricsExperiments | ExperimentsGrowthAnalyticsValidation |