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Criterion
Paper illustration showing three sorted card stacks and an open question about a possible group.
UX Research
Card Sorting
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration of a branching category tree with a highlighted search path and possible dead ends.
UX Research
Tree Testing
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.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 two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects.
Complexitydifferent
LowMediumMediumHigh
Timedifferent
20-45 min45-60 min1-2 Tage1-4 Wochen
Participantsdifferent
Based on research question2-8Based on research question1-6
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncAsync
Outputdifferent
Content groups, Label set, IA hypothesesAssumption map, Test backlog, Risk rankingFindability Metrics, Path Analysis, Revised IAExperiment results, Decision log, Learning summary
Tagsno overlap
Information architectureNavigationStructure
AssumptionsRiskExperimentsValidation
Information architectureNavigationFindability
ExperimentsGrowthAnalyticsValidation
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