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| Criterion |  Decision Making Argument Mapping |  Knowledge Modeling Event Modeling |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | 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. | 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 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 | 1-3 h | 2-6 h | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 1-8 | 2-8 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | Argument Map, Evidence Gaps, Decision Rationale | Event Model, UI Flow, Commands, Read Models | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | SensemakingDecisionRationale | EventsBlueprintDomain-Driven DesignBehavior | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |