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| Criterion |  Product Discovery Hypothesis Prioritization Canvas |  Domain Modeling EventStorming |  UX Research Affinity Diagramming |
|---|---|---|---|
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. | When research notes, feedback, or observations sit unconnected side by side, affinity diagramming sorts the raw material into solid themes. Many individual points turn into patterns that make decisions and opportunities clearer. |
Complexitydifferent | Medium | Medium | Low |
Timedifferent | 60-90 min | 2-8 h | 45–90 min |
Participantsdifferent | 3-8 | 5-12 | 3-10 |
Formatsame | Workshop | Workshop | Workshop |
Outputdifferent | Prioritization Canvas, Hypothesis Backlog | Event Timeline, Ubiquitous Language, Boundaries, Open Questions | Theme clusters, Insight statements, Opportunity areas |
Tagsno overlap | ExperimentsPrioritizationDiscoveryHypothesis | Domain-Driven DesignEventsDiscoveryWorkshop | SynthesisQualitativeRoot cause |
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