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Selected:Outcome-Driven InnovationTree TestingCard SortingDesign Thinking
Criterion
Paper illustration of Outcome-Driven Innovation with its method-specific working model.
Product Discovery
Outcome-Driven Innovation
Paper illustration of a branching category tree with a highlighted search path and possible dead ends.
UX Research
Tree Testing
Paper illustration showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
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
Purposedifferent
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 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 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.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
HighMediumLowHigh
Timedifferent
Mehrere Wochen1-2 Tage20-45 min1 Tag bis mehrere Wochen
Participantsdifferent
2-6 researchers plus sampleBased on research questionBased on research question4-10
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop
Outputdifferent
Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypothesesFindability Metrics, Path Analysis, Revised IAContent groups, Label set, IA hypothesesProblem Statement, Prototype, Test Learnings
Tagsno overlap
OutcomesInnovationResearchQuantitative
Information architectureNavigationFindability
Information architectureNavigationStructure
InnovationPrototypeResearch
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