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Criterion
First-click Testing method illustration showing its working structure
UX Research
First-click 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
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
Purposedifferent
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.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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog.
Complexitydifferent
LowHighLowMedium
Timedifferent
1-2 Tage1-4 Wochen30-60 min60-90 min
Participantsdifferent
10-301-61-53-8
Formatdifferent
AsyncAsyncWorkshop + asyncWorkshop
Outputdifferent
Click Heatmap, Success Rate, Design RecommendationsExperiment results, Decision log, Learning summaryCompleted Experiment Canvas, Success MetricPrioritization Canvas, Hypothesis Backlog
Tagsno overlap
UXNavigationFindabilityValidation
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
ExperimentsPrioritizationDiscoveryHypothesis
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