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| Criterion |  Engineering Hypothesis-Driven Troubleshooting |  Product Discovery Pretotyping |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When systems fail unexpectedly, spontaneous attempts often produce more noise than insight. Hypothesis-driven Troubleshooting translates symptoms into testable assumptions and makes troubleshooting learnable. | 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 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 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 | 30-240 min | Stunden bis wenige Tage | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 1-6 | 1-4 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | Hypothesis Log, Test Plan, Evidence Notes, Diagnosis Summary | Pretotyping sketch, Test setup, Conversion data, Go or no-go decision | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | TroubleshootingProblem solvingDiagnosis | ValidationDemandMVP | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |