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| Criterion |  Knowledge Modeling Event Modeling |  Product Discovery Experiment Canvas |  Growth A/B Testing |  Domain Modeling EventStorming |
|---|---|---|---|---|
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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | 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 a domain consists of many events, rules, and states, it creates a shared modeling space for the team. It bundles language, flows, and boundaries before domain knowledge fragments into siloed views. |
Complexitydifferent | Medium | Low | High | Medium |
Timedifferent | 2-6 h | 30-60 min | 1-4 Wochen | 2-8 h |
Participantsdifferent | 2-8 | 1-5 | 1-6 | 5-12 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop |
Outputdifferent | Event Model, UI Flow, Commands, Read Models | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary | Event Timeline, Ubiquitous Language, Boundaries, Open Questions |
Tagsno overlap | EventsBlueprintDomain-Driven DesignBehavior | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation | Domain-Driven DesignEventsDiscoveryWorkshop |