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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of a branching category tree with a highlighted search path and possible dead ends.
UX Research
Tree Testing
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Purposedifferent
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 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 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.The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.
Complexitydifferent
HighMediumMediumLow
Timedifferent
1-4 Wochen1-2 Tage1-5 Tage25-40 min
Participantsdifferent
1-6Based on research questionNutzertraffic1-5
Formatdifferent
AsyncAsyncAsyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryFindability Metrics, Path Analysis, Revised IAClick Data, Interest Signal, Learning DecisionLearning Card with evidence and next action
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
Information architectureNavigationFindability
ValidationExperimentsDemandDiscovery
ExperimentsValidationDiscoveryLearning
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