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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of Goal Question Metric with its method-specific working model.
Engineering
Goal Question Metric
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.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.Helps clarify technical problems, hypotheses, and next steps in concrete terms. It breaks a technical problem into testable parts. The result is captured as a GQM table and metric briefs.
Complexitydifferent
HighMediumMedium
Timedifferent
1-4 Wochen1-5 Tage90-180 min
Participantsdifferent
1-6Nutzertraffic3-6
Formatdifferent
AsyncAsyncWorkshop
Outputdifferent
Experiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning DecisionGQM Table, Metric Profiles
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
MetricsMeasurementEngineeringAlignment
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Often compared together

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

Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration of Counter Metrics with its method-specific working model.
Product Strategy
Counter Metrics
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration of KPI Tree with its method-specific working model.
Product Strategy
KPI Tree