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Criterion
Visual Management workspace showing the question, observations, and next decision.
Operations
Visual Management
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
With high tempo and many parallel topics, the method makes status, deviations, and priorities visible at a glance. It reduces search effort and prevents what matters from getting lost in daily work.When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses.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.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.
Complexitydifferent
LowMediumMediumHigh
Timedifferent
Ongoing1-3 h1-5 Tage1-4 Wochen
Participantsdifferent
1-201-5Nutzertraffic1-6
Formatdifferent
Workshop + asyncAsyncAsyncAsync
Outputdifferent
Visual Board, Status Indicators, Exception CuesFunnel report, Drop-off analysis, Optimization hypothesesClick Data, Interest Signal, Learning DecisionExperiment results, Decision log, Learning summary
Tagsno overlap
SignalsOperationsVisual management
AnalyticsConversionGrowth
ValidationExperimentsDemandDiscovery
ExperimentsGrowthAnalyticsValidation
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