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| Criterion |  Growth A/B Testing |  Growth Hooked Model |  Product Strategy Counter Metrics |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | 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. | The Hooked Model helps clarify engagement loops, user behavior, and experiments. It makes repeat behavior measurable and captures the result as a hooked loop, trigger map, and reward design. | 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | High | Medium | Low | Low |
Timedifferent | 1-4 Wochen | Multiple workshops over several weeks | 30-60 min | 1-5 Tage |
Participantsdifferent | 1-6 | 2-8 | 2-6 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Hooked loop, Trigger map, Reward design, Ethics check | Counter Metric List, Guardrail Definitions | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | GrowthBehaviorRetention | MetricsMeasurementStrategyExperiments | ValidationExperimentsDemandGrowth |