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| Criterion |  UX Research Tree Testing |  Innovation Design Sprint |  Innovation Design Thinking |  Product Discovery Outcome-Driven Innovation |
|---|---|---|---|---|
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. | 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. | Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs. |
Complexitydifferent | Medium | High | High | High |
Timedifferent | 1-2 Tage | 4-5 Tage | 1 Tag bis mehrere Wochen | Mehrere Wochen |
Participantsdifferent | Based on research question | 5-8 | 4-10 | 2-6 researchers plus sample |
Formatdifferent | Async | Workshop | Workshop | Workshop + async |
Outputdifferent | Findability Metrics, Path Analysis, Revised IA | Prototype, Test Findings, Decision Rationale | Problem Statement, Prototype, Test Learnings | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses |
Tagsno overlap | Information architectureNavigationFindability | Design sprintPrototypeValidationInnovation | InnovationPrototypeResearch | OutcomesInnovationResearchQuantitative |