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| Criterion |  Growth Funnel Analysis |  Product Discovery Smoke Test |  Engineering Goal Question Metric |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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. | Helps clarify technical problems, hypotheses, and next steps in concrete terms. It breaks a technical problem into testable parts. The result is captured as a GQM table and metric briefs. | 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 | Medium | High |
Timedifferent | 1-3 h | 1-5 Tage | 90-180 min | 1-4 Wochen |
Participantsdifferent | 1-5 | Nutzertraffic | 3-6 | 1-6 |
Formatdifferent | Async | Async | Workshop | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Interest Metrics, Conversion Signal, Learning Note | GQM Table, Metric Profiles | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | ValidationExperimentsDemandGrowth | MetricsMeasurementEngineeringAlignment | ExperimentsGrowthAnalyticsValidation |