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| Criterion |  Product Discovery Opportunity Scoring |  Agile Affinity Estimation |  Product Discovery Opportunity Solution Tree |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When opportunities need ranking by their effect, it makes importance and satisfaction directly comparable. It separates problem, assumption, solution, and evidence. The result is captured as an opportunity-score table and top outcomes. | When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. | 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 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 | Medium | Medium | Low |
Timedifferent | 60-120 min | 30-90 min | 1-2 h Setup, laufend | 30-60 min |
Participantsdifferent | 3-6 | 3-12 | 2-6 | 1-5 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Opportunity Score Table, Top Outcomes | Affinity Size Map, Grouped Estimates, Unclear Items | Opportunity Solution Tree, Experiment Backlog, Learning Log | Completed Experiment Canvas, Success Metric |
Tagsno overlap | PrioritizationDiscoveryOutcomesNeeds | EstimationBacklogRelative sizing | DiscoveryOutcomesExperimentsOpportunity | ExperimentsValidationDiscoveryHypothesis |