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| Criterion |  UX Research Affinity Diagramming |  Product Discovery Concierge MVP |  Product Discovery Experiment Canvas |  Product Discovery Fake Door Test |
|---|---|---|---|---|
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 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 | Medium | Low | Medium |
Timedifferent | 45–90 min | 1-4 Wochen | 30-60 min | 1-5 Tage |
Participantsdifferent | 3-10 | 3-10 Kunden | 1-5 | Nutzertraffic |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Async |
Outputdifferent | Theme clusters, Insight statements, Opportunity areas | Concierge Learnings, Service Blueprint, MVP Risks | Completed Experiment Canvas, Success Metric | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | SynthesisQualitativeRoot cause | MVPValidationServiceDiscovery | ExperimentsValidationDiscoveryHypothesis | ValidationExperimentsDemandDiscovery |