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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 Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
Paper illustration of a Test Card with four fields for hypothesis, test, metric, and success threshold.
Product Discovery
Test 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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog.The Test Card turns a critical assumption into a testable claim and specifies in advance which result counts as success.
Complexitydifferent
HighMediumMediumLow
Timedifferent
1-4 Wochen1-2 Tage60-90 min20-35 min
Participantsdifferent
1-6Based on research question3-81-5
Formatdifferent
AsyncAsyncWorkshopWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryFindability Metrics, Path Analysis, Revised IAPrioritization Canvas, Hypothesis BacklogTest Card with a pre-set threshold
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
Information architectureNavigationFindability
ExperimentsPrioritizationDiscoveryHypothesis
ExperimentsValidationDiscoveryHypothesis
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