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| Criterion |  UX Research Surveys |  UX Research Affinity Diagramming |  UX Research Tree Testing |  Product Discovery Outcome-Driven Innovation |
|---|---|---|---|---|
Purposedifferent | 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. | When research notes, feedback, or observations sit unconnected side by side, affinity diagramming sorts the raw material into solid themes. Many individual points turn into patterns that make decisions and opportunities clearer. | 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. | 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 | Low | Medium | High |
Timedifferent | 3-14 Tage | 45–90 min | 1-2 Tage | Mehrere Wochen |
Participantsdifferent | 50+ | 3-10 | Based on research question | 2-6 researchers plus sample |
Formatdifferent | Async | Workshop | Async | Workshop + async |
Outputdifferent | Survey Results, Charts, Segment Insights | Theme clusters, Insight statements, Opportunity areas | Findability Metrics, Path Analysis, Revised IA | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses |
Tagsno overlap | QuantitativeResearchValidation | SynthesisQualitativeRoot cause | Information architectureNavigationFindability | OutcomesInnovationResearchQuantitative |