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| Criterion |  Product Discovery Kano Model |  Product Discovery Opportunity Solution Tree |  Product Discovery Opportunity Scoring |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When features need to be distinguished by their effect on satisfaction, it makes expectations and surprises comparable. It separates basic needs, performance contribution, and delight. | 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 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 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 | 1-2 Tage | 1-2 h Setup, laufend | 60-120 min | 30-60 min |
Participantsdifferent | 10-50 | 2-6 | 3-6 | 1-5 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Opportunity Solution Tree, Experiment Backlog, Learning Log | Opportunity Score Table, Top Outcomes | Completed Experiment Canvas, Success Metric |
Tagsno overlap | SatisfactionPrioritizationCustomer | DiscoveryOutcomesExperimentsOpportunity | PrioritizationDiscoveryOutcomesNeeds | ExperimentsValidationDiscoveryHypothesis |