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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 of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
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.The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.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.
Complexitydifferent
HighMediumLowLow
Timedifferent
1-4 Wochen1-2 Tage25-40 min30-60 min
Participantsdifferent
1-6Based on research question1-51-5
Formatdifferent
AsyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryFindability Metrics, Path Analysis, Revised IALearning Card with evidence and next actionCompleted Experiment Canvas, Success Metric
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
Information architectureNavigationFindability
ExperimentsValidationDiscoveryLearning
ExperimentsValidationDiscoveryHypothesis
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