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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 Smoke Test.
Product Discovery
Smoke Test
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.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 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.
Complexitydifferent
MediumLowMediumHigh
Timedifferent
1-2 Tage1-5 Tage1-5 Tage1-4 Wochen
Participantsdifferent
Based on research questionNutzertrafficNutzertraffic1-6
Formatsame
AsyncAsyncAsyncAsync
Outputdifferent
Findability Metrics, Path Analysis, Revised IAInterest Metrics, Conversion Signal, Learning NoteClick Data, Interest Signal, Learning DecisionExperiment results, Decision log, Learning summary
Tagsno overlap
Information architectureNavigationFindability
ValidationExperimentsDemandGrowth
ValidationExperimentsDemandDiscovery
ExperimentsGrowthAnalyticsValidation
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