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| Criterion |  Domain Modeling Context Map |  Growth Funnel Analysis |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When several contexts need to talk to each other, it makes their relationships and dependencies legible. It helps sort integration pressure and responsibilities across system boundaries. | 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. | 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 | Medium | Low | High |
Timedifferent | 1-3 h | 1-3 h | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | 1-5 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Async | Async | Async |
Outputdifferent | Context Map, Integration Patterns, Boundary Notes | Funnel report, Drop-off analysis, Optimization hypotheses | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | Domain-Driven DesignBoundariesStrategy | AnalyticsConversionGrowth | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |