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| Criterion |  Product Discovery Kano Model |  Product Discovery Concierge MVP |  Product Discovery Problem Interview |  Product Discovery Hypothesis Prioritization 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 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 the picture of the problem still needs to become solid, it asks about real situations and consequences. It separates genuine suffering from mere interest in a solution. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 1-2 Tage | 1-4 Wochen | 30-60 min je Interview | 60-90 min |
Participantsdifferent | 10-50 | 3-10 Kunden | 5-12 Interviews | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Kano Matrix, Feature Classes, Priority Themes | Concierge Learnings, Service Blueprint, MVP Risks | Problem Evidence, Risk Notes, Customer Segments | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | SatisfactionPrioritizationCustomer | MVPValidationServiceDiscovery | DiscoveryInterviewsValidation | ExperimentsPrioritizationDiscoveryHypothesis |