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| Criterion |  Engineering Goal Question Metric |  UX Research HEART Framework |  Product Discovery Assumption Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | Helps clarify technical problems, hypotheses, and next steps in concrete terms. It breaks a technical problem into testable parts. The result is captured as a GQM table and metric briefs. | 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. | 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 | 90-180 min | 120 min initial, dann laufend | 45-60 min | 1-4 Wochen |
Participantsdifferent | 3-6 | 3-6 | 2-8 | 1-6 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Async |
Outputdifferent | GQM Table, Metric Profiles | HEART-GSM Table, Dashboard | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | MetricsMeasurementEngineeringAlignment | MetricsUX researchMeasurementSatisfaction | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |