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| Criterion |  Decision Making PERT Estimation |  Growth Hooked Model |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | On complex initiatives, a plain average tends to understate just how uncertain the outcome really is. It separates options, evaluation criteria, and open risks. The result is captured as a PERT Estimate, Expected Value, and Risk Notes. | 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 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. | 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 | Medium | Medium | High | Low |
Timedifferent | 15-45 min | Multiple workshops over several weeks | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 1-8 | 2-8 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | PERT Estimate, Expected Value, Risk Notes | Hooked loop, Trigger map, Reward design, Ethics check | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | EstimationUncertaintyRisk | GrowthBehaviorRetention | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |