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| Criterion |  UX Research Tree Testing |  Innovation Design Thinking |  Product Discovery Outcome-Driven Innovation |  UX Research Surveys |
|---|---|---|---|---|
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 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. | When a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal. |
Complexitydifferent | Medium | High | High | Medium |
Timedifferent | 1-2 Tage | 1 Tag bis mehrere Wochen | Mehrere Wochen | 3-14 Tage |
Participantsdifferent | Based on research question | 4-10 | 2-6 researchers plus sample | 50+ |
Formatdifferent | Async | Workshop | Workshop + async | Async |
Outputdifferent | Findability Metrics, Path Analysis, Revised IA | Problem Statement, Prototype, Test Learnings | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Survey Results, Charts, Segment Insights |
Tagsno overlap | Information architectureNavigationFindability | InnovationPrototypeResearch | OutcomesInnovationResearchQuantitative | QuantitativeResearchValidation |