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| Criterion |  Product Discovery Smoke Test |  Product Strategy Counter Metrics |  Product Strategy Impact Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions. | When a goal needs to be connected to several possible paths, it shows chains of impact instead of feature lists. It connects business goal, behavior change, and measures. | 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 | 1-5 Tage | 30-60 min | 45-90 min | 1-4 Wochen |
Participantsdifferent | Nutzertraffic | 2-6 | 3-8 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Interest Metrics, Conversion Signal, Learning Note | Counter Metric List, Guardrail Definitions | Impact Map, Outcome Hypotheses, Delivery Options | Experiment results, Decision log, Learning summary |
Tagsno overlap | ValidationExperimentsDemandGrowth | MetricsMeasurementStrategyExperiments | OutcomesStrategyBehaviorPlanning | ExperimentsGrowthAnalyticsValidation |