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| Criterion |  Product Discovery Hypothesis Prioritization Canvas |  Domain Modeling EventStorming |  Knowledge Modeling Domain Storytelling |  Product Discovery Fake Door Test |
|---|---|---|---|---|
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. | 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. | Domain Storytelling translates domain knowledge into a shared narrative of actors, objects, and workflows. It is especially useful when language, rules, and process understanding must be tightly connected. | 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. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | 60-90 min | 2-8 h | 1-2 h | 1-5 Tage |
Participantsdifferent | 3-8 | 5-12 | 2-8 | Nutzertraffic |
Formatdifferent | Workshop | Workshop | Workshop | Async |
Outputdifferent | Prioritization Canvas, Hypothesis Backlog | Event Timeline, Ubiquitous Language, Boundaries, Open Questions | Domain Story, Glossary Notes, Process Narrative | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsPrioritizationDiscoveryHypothesis | Domain-Driven DesignEventsDiscoveryWorkshop | KnowledgeDomain-Driven DesignProcess | ValidationExperimentsDemandDiscovery |