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| Criterion |  Product Discovery Hypothesis Prioritization Canvas |  Knowledge Modeling Event Modeling |  Product Discovery Fake Door Test |  Domain Modeling EventStorming |
|---|---|---|---|---|
Purposedifferent | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | 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 is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. | 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 60-90 min | 2-6 h | 1-5 Tage | 2-8 h |
Participantsdifferent | 3-8 | 2-8 | Nutzertraffic | 5-12 |
Formatdifferent | Workshop | Workshop + async | Async | Workshop |
Outputdifferent | Prioritization Canvas, Hypothesis Backlog | Event Model, UI Flow, Commands, Read Models | Click Data, Interest Signal, Learning Decision | Event Timeline, Ubiquitous Language, Boundaries, Open Questions |
Tagsno overlap | ExperimentsPrioritizationDiscoveryHypothesis | EventsBlueprintDomain-Driven DesignBehavior | ValidationExperimentsDemandDiscovery | Domain-Driven DesignEventsDiscoveryWorkshop |