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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Ivy Lee Method
Operations
Ivy Lee Method
Paper illustration for Smoke Test.
Product Discovery
Smoke 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.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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.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
HighLowLowLow
Timedifferent
1-4 Wochen5-10 min daily1-5 Tage30-60 min
Participantsdifferent
1-61Nutzertraffic1-5
Formatdifferent
AsyncAsyncAsyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryDaily Priority List, Completion NotesInterest Metrics, Conversion Signal, Learning NoteCompleted Experiment Canvas, Success Metric
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
PrioritizationProductivityExecution
ValidationExperimentsDemandGrowth
ExperimentsValidationDiscoveryHypothesis
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