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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
Paper illustration for Ivy Lee Method
Operations
Ivy Lee Method
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.With a restless workday full of too many open items, the method creates radical simplicity. It directs attention to a short sequence instead of a broad, still-open field.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 Wochen1-5 Tage5-10 min daily30-60 min
Participantsdifferent
1-6Nutzertraffic11-5
Formatdifferent
AsyncAsyncAsyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning DecisionDaily Priority List, Completion NotesCompleted Experiment Canvas, Success Metric
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
PrioritizationProductivityExecution
ExperimentsValidationDiscoveryHypothesis
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