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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Causal Loop Diagram workspace showing the question, observations, and next decision.
Systems Thinking
Causal Loop Diagram
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.A Causal Loop Diagram makes feedback, reinforcement, and balance in a system legible. It uncovers side effects and self-reinforcement that stay hidden in linear explanations.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
HighMediumLowMedium
Timedifferent
1-4 Wochen1-3 h1-5 Tage1-5 Tage
Participantsdifferent
1-62-8NutzertrafficNutzertraffic
Formatdifferent
AsyncWorkshopAsyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryCausal Loop Diagram, Feedback Notes, Leverage PointsInterest Metrics, Conversion Signal, Learning NoteClick Data, Interest Signal, Learning Decision
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
FeedbackSystems thinkingCausalityDynamics
ValidationExperimentsDemandGrowth
ValidationExperimentsDemandDiscovery
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