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| Criterion |  UX Research Tree Testing |  Innovation Design Sprint |  Product Discovery Concierge MVP |  Innovation Design Thinking |
|---|---|---|---|---|
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 product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | 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. | For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service. |
Complexitydifferent | Medium | High | Medium | High |
Timedifferent | 1-2 Tage | 4-5 Tage | 1-4 Wochen | 1 Tag bis mehrere Wochen |
Participantsdifferent | Based on research question | 5-8 | 3-10 Kunden | 4-10 |
Formatdifferent | Async | Workshop | Workshop + async | Workshop |
Outputdifferent | Findability Metrics, Path Analysis, Revised IA | Prototype, Test Findings, Decision Rationale | Concierge Learnings, Service Blueprint, MVP Risks | Problem Statement, Prototype, Test Learnings |
Tagsno overlap | Information architectureNavigationFindability | Design sprintPrototypeValidationInnovation | MVPValidationServiceDiscovery | InnovationPrototypeResearch |