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| Criterion |  Engineering Kanban |  Growth Funnel Analysis |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | When work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable. | 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 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 | Ongoing | 1-3 h | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 2-12 | 1-5 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Async | Async | Async |
Outputdifferent | Kanban board, WIP policies, Flow metrics | Funnel report, Drop-off analysis, Optimization hypotheses | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | FlowVisual managementDelivery | AnalyticsConversionGrowth | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |