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Selected:Tree TestingDesign ThinkingCard SortingOutcome-Driven Innovation
Criterion
Paper illustration of a branching category tree with a highlighted search path and possible dead ends.
UX Research
Tree Testing
Design Thinking as a learning loop: an observation notebook, a focused problem statement, different idea sketches, a cardboard prototype and user-test notes. Feedback leads to new understanding.
Innovation
Design Thinking
Paper illustration showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
Paper illustration of Outcome-Driven Innovation with its method-specific working model.
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.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.When content only makes sense internally and users can't find the structure again, card sorting exposes their mental order. Terms, groups, and naming are then aligned with the target group's expectations.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
MediumHighLowHigh
Timedifferent
1-2 Tage1 Tag bis mehrere Wochen20-45 minMehrere Wochen
Participantsdifferent
Based on research question4-10Based on research question2-6 researchers plus sample
Formatdifferent
AsyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Findability Metrics, Path Analysis, Revised IAProblem Statement, Prototype, Test LearningsContent groups, Label set, IA hypothesesDesired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses
Tagsno overlap
Information architectureNavigationFindability
InnovationPrototypeResearch
Information architectureNavigationStructure
OutcomesInnovationResearchQuantitative
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