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Criterion
Paper illustration of Lean Startup with its method-specific working model.
Innovation
Lean Startup
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
For uncertain business assumptions, the method forces the idea into contact with real market reactions early. It separates wishful picture, assumption, and observable behavior, so that learning becomes faster than planning. This translates uncertainty into measurable insight.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
MediumMediumMediumHigh
Timedifferent
Wochen bis Monate je Lernzyklus1-3 h1-5 Tage1-4 Wochen
Participantsdifferent
2-81-5Nutzertraffic1-6
Formatdifferent
Workshop + asyncAsyncAsyncAsync
Outputdifferent
Hypothesis list, MVPs, Learning reports, Pivot or persevere decisionFunnel report, Drop-off analysis, Optimization hypothesesClick Data, Interest Signal, Learning DecisionExperiment results, Decision log, Learning summary
Tagsno overlap
LeanStartupValidationMVP
AnalyticsConversionGrowth
ValidationExperimentsDemandDiscovery
ExperimentsGrowthAnalyticsValidation
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