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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of a Lean Canvas with nine fields, notes, and one highlighted learning risk.
Product Strategy
Lean Canvas
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
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 early product bet still has too many open points, it brings target group, problem, and assumptions into a single view. It condenses the idea so core risks become nameable.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 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.
Complexitydifferent
HighMediumLowMedium
Timedifferent
1-4 Wochen45-90 min1-5 Tage1-5 Tage
Participantsdifferent
1-61-6NutzertrafficNutzertraffic
Formatdifferent
AsyncWorkshop + asyncAsyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryLean Canvas, Core Assumptions, Experiment BacklogInterest Metrics, Conversion Signal, Learning NoteClick Data, Interest Signal, Learning Decision
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
StartupLeanAssumptionsBusiness model
ValidationExperimentsDemandGrowth
ValidationExperimentsDemandDiscovery
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