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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
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 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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.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 Wochen1-5 Tage1-2 Wochen30-60 min
Participantsdifferent
1-6Nutzertraffic1-61-5
Formatdifferent
AsyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning DecisionExperiment card, Result summary, Next betCompleted Experiment Canvas, Success Metric
Tags1 shared
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
MarketingGrowthExperimentsLearning
ExperimentsValidationDiscoveryHypothesis
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