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| Criterion |  Knowledge Modeling Event Modeling |  Product Discovery Smoke Test |  Decision Making Argument Mapping |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | Event Modeling connects business workflows with commands, events, and views into one coherent mental model. It helps design behavior, UI, and technical slices from the same underlying logic. | 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 statements, evidence, and counterarguments get mixed up, a debate quickly loses its structure. Argument Mapping breaks a thesis down into its reasoning and makes visible what it really rests on. | 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 | 2-6 h | 1-5 Tage | 1-3 h | 1-4 Wochen |
Participantsdifferent | 2-8 | Nutzertraffic | 1-8 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | Event Model, UI Flow, Commands, Read Models | Interest Metrics, Conversion Signal, Learning Note | Argument Map, Evidence Gaps, Decision Rationale | Experiment results, Decision log, Learning summary |
Tagsno overlap | EventsBlueprintDomain-Driven DesignBehavior | ValidationExperimentsDemandGrowth | SensemakingDecisionRationale | ExperimentsGrowthAnalyticsValidation |