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| Criterion |  UX Research Affinity Diagramming |  Product Discovery Concierge MVP |  Product Discovery Experiment Canvas |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | 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. | When an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. | 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 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. |
Complexitydifferent | Low | Medium | Low | Medium |
Timedifferent | 45–90 min | 1-4 Wochen | 30-60 min | 60-90 min |
Participantsdifferent | 3-10 | 3-10 Kunden | 1-5 | 3-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Theme clusters, Insight statements, Opportunity areas | Concierge Learnings, Service Blueprint, MVP Risks | Completed Experiment Canvas, Success Metric | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | SynthesisQualitativeRoot cause | MVPValidationServiceDiscovery | ExperimentsValidationDiscoveryHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |