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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for PDCA Cycle.
Operations
PDCA Cycle
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 an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode.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
HighLowLow
Timedifferent
1-4 Wochen1 h bis mehrere Wochen1-5 Tage
Participantsdifferent
1-61-8Nutzertraffic
Formatdifferent
AsyncWorkshop + asyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryPDCA Log, Experiment Plan, Learning Outcome, Standard ChangeInterest Metrics, Conversion Signal, Learning Note
Tags1 shared
ExperimentsGrowthAnalyticsValidation
Continuous improvementLeanExperiments
ValidationExperimentsDemandGrowth
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Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis