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| Criterion |  Knowledge Modeling Domain Storytelling |  Product Discovery Smoke Test |  Product Discovery Hypothesis Prioritization Canvas |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | 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 only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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 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 | Low | Low | Medium | Medium |
Timedifferent | 1-2 h | 1-5 Tage | 60-90 min | 1-5 Tage |
Participantsdifferent | 2-8 | Nutzertraffic | 3-8 | Nutzertraffic |
Formatdifferent | Workshop | Async | Workshop | Async |
Outputdifferent | Domain Story, Glossary Notes, Process Narrative | Interest Metrics, Conversion Signal, Learning Note | Prioritization Canvas, Hypothesis Backlog | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | KnowledgeDomain-Driven DesignProcess | ValidationExperimentsDemandGrowth | ExperimentsPrioritizationDiscoveryHypothesis | ValidationExperimentsDemandDiscovery |