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| Criterion |  Operations Change Analysis |  Product Discovery Experiment Canvas |  UX Research Affinity Diagramming |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | For a deviation after a change, the method isolates the influence of the altered condition. It narrows down which differences are relevant and which are just accompanying noise. | 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 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 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 | Low | Low | Medium |
Timedifferent | 45-120 min | 30-60 min | 45–90 min | 1-5 Tage |
Participantsdifferent | 2-6 | 1-5 | 3-10 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Async |
Outputdifferent | Change Matrix, Cause Hypotheses, Validation Questions, Action List | Completed Experiment Canvas, Success Metric | Theme clusters, Insight statements, Opportunity areas | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ChangeRoot causeTroubleshootingComparison | ExperimentsValidationDiscoveryHypothesis | SynthesisQualitativeRoot cause | ValidationExperimentsDemandDiscovery |