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| Criterion |  Product Discovery Opportunity Solution Tree |  UX Research Affinity Diagramming |  Architecture C4 Model |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure. | 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. | The C4 Model makes a system legible across several resolution levels, from context down to code. It suits situations where different audiences need to understand the same architecture from different altitudes. | 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. |
Complexitydifferent | Medium | Low | Low | Low |
Timedifferent | 1-2 h Setup, laufend | 45–90 min | 1-4 h | 30-60 min |
Participantsdifferent | 2-6 | 3-10 | 1-5 | 1-5 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Opportunity Solution Tree, Experiment Backlog, Learning Log | Theme clusters, Insight statements, Opportunity areas | Context Diagram, Container Diagram, Component Diagram | Completed Experiment Canvas, Success Metric |
Tagsno overlap | DiscoveryOutcomesExperimentsOpportunity | SynthesisQualitativeRoot cause | ArchitectureCommunicationVisualization | ExperimentsValidationDiscoveryHypothesis |