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| Criterion |  Product Strategy ICE Scoring |  UX Research HEART Framework |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list. | 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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 | Low | Medium | Low | High |
Timedifferent | 30-60 min | 120 min initial, dann laufend | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | 3-6 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | ICE Table, Top Idea List | HEART-GSM Table, Dashboard | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationScoringGrowthDecision | MetricsUX researchMeasurementSatisfaction | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |