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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
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
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.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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.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
MediumHighLowLow
Timedifferent
1-2 Tage1-4 Wochen30-60 min1-2 Tage
Participantsdifferent
Based on research question1-61-510-30
Formatdifferent
AsyncAsyncWorkshop + asyncAsync
Outputdifferent
Findability Metrics, Path Analysis, Revised IAExperiment results, Decision log, Learning summaryCompleted Experiment Canvas, Success MetricClick Heatmap, Success Rate, Design Recommendations
Tagsno overlap
Information architectureNavigationFindability
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
UXNavigationFindabilityValidation
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