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| Criterion |  Engineering Golden Path |  Product Discovery Smoke Test |  Product Discovery Pretotyping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When teams need a reliable default path for frequent use, sprawl quickly emerges without any guiding logic. Golden Path bundles the preferred path so good practice becomes easy and deviation becomes deliberate. | 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. | Pretotyping clarifies whether a customer problem and solution idea create enough real demand. It separates problem, assumption, solution, and evidence, and captures the result as a pretotyping sketch, test setup, and conversion data. | 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 | Medium | Low | Low | High |
Timedifferent | 1-3 Tage Setup, laufend | 1-5 Tage | Stunden bis wenige Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | Nutzertraffic | 1-4 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | Golden Path Guide, Templates, Quality Checks | Interest Metrics, Conversion Signal, Learning Note | Pretotyping sketch, Test setup, Conversion data, Go or no-go decision | Experiment results, Decision log, Learning summary |
Tagsno overlap | EngineeringProductivityGovernance | ValidationExperimentsDemandGrowth | ValidationDemandMVP | ExperimentsGrowthAnalyticsValidation |