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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
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
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 many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses.When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.
Complexitydifferent
LowHighMediumMedium
Timedifferent
1-2 Tage1-4 Wochen1-3 h1-5 Tage
Participantsdifferent
10-301-61-5Nutzertraffic
Formatsame
AsyncAsyncAsyncAsync
Outputdifferent
Click Heatmap, Success Rate, Design RecommendationsExperiment results, Decision log, Learning summaryFunnel report, Drop-off analysis, Optimization hypothesesClick Data, Interest Signal, Learning Decision
Tagsno overlap
UXNavigationFindabilityValidation
ExperimentsGrowthAnalyticsValidation
AnalyticsConversionGrowth
ValidationExperimentsDemandDiscovery
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