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| Criterion |  Operations ABC Analysis |  Product Discovery Smoke Test |  Product Strategy KPI Tree |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | With many similar objects of differing economic significance, the method prioritizes effort by effect. It separates what needs regular steering from what rarely needs attention. | 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 metrics across the organization drift apart, it arranges drivers and effects under one shared logic. It connects customer value, product logic, and decision priorities. The result is captured as a KPI tree and owner list. | 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 | Low | Medium | High |
Timedifferent | 30-60 min | 1-5 Tage | 90-180 min initial, dann laufend | 1-4 Wochen |
Participantsdifferent | 1-5 | Nutzertraffic | 3-8 | 1-6 |
Formatdifferent | Async | Async | Workshop + async | Async |
Outputdifferent | ABC Classification, Focus Rules, Control List | Interest Metrics, Conversion Signal, Learning Note | KPI Tree, Owner List | Experiment results, Decision log, Learning summary |
Tagsno overlap | PrioritizationOperationsPortfolio | ValidationExperimentsDemandGrowth | MetricsStrategyAlignmentMeasurement | ExperimentsGrowthAnalyticsValidation |