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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
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.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 h1-2 Wochen1-4 Wochen
Participantsdifferent
2-81-51-61-6
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
Hypothesis list, MVPs, Learning reports, Pivot or persevere decisionFunnel report, Drop-off analysis, Optimization hypothesesExperiment card, Result summary, Next betExperiment results, Decision log, Learning summary
Tagsno overlap
LeanStartupValidationMVP
AnalyticsConversionGrowth
MarketingGrowthExperimentsLearning
ExperimentsGrowthAnalyticsValidation
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