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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.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 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
HighMediumMediumLow
Timedifferent
1-4 Wochen1-2 Wochen pro Iteration1-5 Tage30-60 min
Participantsdifferent
1-62-6Nutzertraffic1-5
Formatdifferent
AsyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryPrioritized Assumption List, Test Plan, Results ReportClick Data, Interest Signal, Learning DecisionCompleted Experiment Canvas, Success Metric
Tags2 shared
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryAssumptions
ValidationExperimentsDemandDiscovery
ExperimentsValidationDiscoveryHypothesis
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