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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 for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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 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.When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
MediumHighMediumLow
Timedifferent
1-2 Tage1-4 Wochen1-5 Tage1-5 Tage
Participantsdifferent
Based on research question1-6NutzertrafficNutzertraffic
Formatsame
AsyncAsyncAsyncAsync
Outputdifferent
Findability Metrics, Path Analysis, Revised IAExperiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning DecisionInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
Information architectureNavigationFindability
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
ValidationExperimentsDemandGrowth
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