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Criterion
Paper illustration of a branching category tree with a highlighted search path and possible dead ends.
UX Research
Tree Testing
Paper illustration for PDCA Cycle.
Operations
PDCA Cycle
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
First-click Testing method illustration showing its working structure
UX Research
First-click Testing
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 an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode.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.When users immediately turn the wrong way on a screen or wireframe, first click testing checks initial orientation at high speed. The first click shows early whether expectation, labeling, and wayfinding fit together.
Complexitydifferent
MediumLowHighLow
Timedifferent
1-2 Tage1 h bis mehrere Wochen1-4 Wochen1-2 Tage
Participantsdifferent
Based on research question1-81-610-30
Formatdifferent
AsyncWorkshop + asyncAsyncAsync
Outputdifferent
Findability Metrics, Path Analysis, Revised IAPDCA Log, Experiment Plan, Learning Outcome, Standard ChangeExperiment results, Decision log, Learning summaryClick Heatmap, Success Rate, Design Recommendations
Tagsno overlap
Information architectureNavigationFindability
Continuous improvementLeanExperiments
ExperimentsGrowthAnalyticsValidation
UXNavigationFindabilityValidation
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