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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
A 5 Whys working surface connects an observable problem with evidenced causes, marked uncertainty and concrete countermeasures with ownership.
Operations
5 Whys
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.For a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description.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
HighLowLowLow
Timedifferent
1-4 Wochen1 h bis mehrere Wochen15-30 min1-5 Tage
Participantsdifferent
1-61-82-6Nutzertraffic
Formatdifferent
AsyncWorkshop + asyncWorkshopAsync
Outputdifferent
Experiment results, Decision log, Learning summaryPDCA Log, Experiment Plan, Learning Outcome, Standard ChangeRoot cause notes, CountermeasuresInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
Continuous improvementLeanExperiments
Root causeIncidentLeanProblem solving
ValidationExperimentsDemandGrowth
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