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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Lean Startup with its method-specific working model.
Innovation
Lean Startup
Paper illustration for Root Cause Tree Analysis
Operations
Root Cause Tree Analysis
Paper illustration for Smoke Test.
Product Discovery
Smoke 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.For uncertain business assumptions, the method forces the idea into contact with real market reactions early. It separates wishful picture, assumption, and observable behavior, so that learning becomes faster than planning. This translates uncertainty into measurable insight.For a problem with several suspected causes, the method builds a causal structure instead of a mere list. It makes visible how causes connect and where the strongest points of leverage lie.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.
Complexitydifferent
HighMediumMediumLow
Timedifferent
1-4 WochenWochen bis Monate je Lernzyklus1-3 h1-5 Tage
Participantsdifferent
1-62-82-8Nutzertraffic
Formatdifferent
AsyncWorkshop + asyncWorkshopAsync
Outputdifferent
Experiment results, Decision log, Learning summaryHypothesis list, MVPs, Learning reports, Pivot or persevere decisionCause Tree, Evidence Notes, CountermeasuresInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
LeanStartupValidationMVP
Root causeTreeIncidentQuality
ValidationExperimentsDemandGrowth
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