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| Criterion |  UX Research Tree Testing |  Product Discovery Problem Interview |  Product Discovery Hypothesis Prioritization Canvas |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | When a navigation exists but search paths still fail, tree testing checks findability without visual distraction. The method shows whether labels, levels, and paths really lead to the intended destination. | 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. | 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. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 1-2 Tage | 30-60 min je Interview | 60-90 min | 1-5 Tage |
Participantsdifferent | Based on research question | 5-12 Interviews | 3-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Findability Metrics, Path Analysis, Revised IA | Problem Evidence, Risk Notes, Customer Segments | Prioritization Canvas, Hypothesis Backlog | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | Information architectureNavigationFindability | DiscoveryInterviewsValidation | ExperimentsPrioritizationDiscoveryHypothesis | ValidationExperimentsDemandDiscovery |