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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of two considered options leading to a decision record with a marked status and visible consequences.
Architecture
Architecture Decision Record
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
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.An ADR permanently records an architecture decision with context, trade-offs, and consequence. It creates continuity for later changes because the decision path stays traceable.When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.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 Wochen15-45 min30-60 min1-5 Tage
Participantsdifferent
1-61-31-5Nutzertraffic
Formatdifferent
AsyncAsyncWorkshop + asyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryADR File, Decision Log, RationaleCompleted Experiment Canvas, Success MetricClick Data, Interest Signal, Learning Decision
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ArchitectureRationaleDocumentationGovernance
ExperimentsValidationDiscoveryHypothesis
ValidationExperimentsDemandDiscovery
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