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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of RAID Log with a method-specific labelled workspace.
Delivery
RAID Log
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.Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as a RAID Log and a source for status reporting.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
HighLowLowMedium
Timedifferent
1-4 Wochen30 min Setup, dann laufend1-5 Tage1-5 Tage
Participantsdifferent
1-61-3 maintaining, briefing for everyoneNutzertrafficNutzertraffic
Formatsame
AsyncAsyncAsyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryRAID Log, Status Report SourceInterest Metrics, Conversion Signal, Learning NoteClick Data, Interest Signal, Learning Decision
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
RiskTrackingStakeholdersGovernance
ValidationExperimentsDemandGrowth
ValidationExperimentsDemandDiscovery
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