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| Criterion |  UX Research Tree Testing |  Innovation Lean Startup |  Product Discovery Fake Door Test |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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. | For uncertain business assumptions, the method forces the idea into contact with real market reactions early. It separates wishful picture, assumption, and observable behavior, so that learning becomes faster than planning. This translates uncertainty into measurable insight. | 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. | 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 | Wochen bis Monate je Lernzyklus | 1-5 Tage | 30-60 min |
Participantsdifferent | Based on research question | 2-8 | Nutzertraffic | 1-5 |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | Findability Metrics, Path Analysis, Revised IA | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision | Click Data, Interest Signal, Learning Decision | Completed Experiment Canvas, Success Metric |
Tagsno overlap | Information architectureNavigationFindability | LeanStartupValidationMVP | ValidationExperimentsDemandDiscovery | ExperimentsValidationDiscoveryHypothesis |