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Criterion
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration of Lean Startup with its method-specific working model.
Innovation
Lean Startup
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
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.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 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
1-3 hWochen bis Monate je Lernzyklus1-2 Wochen1-4 Wochen
Participantsdifferent
1-52-81-61-6
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesHypothesis list, MVPs, Learning reports, Pivot or persevere decisionExperiment card, Result summary, Next betExperiment results, Decision log, Learning summary
Tagsno overlap
AnalyticsConversionGrowth
LeanStartupValidationMVP
MarketingGrowthExperimentsLearning
ExperimentsGrowthAnalyticsValidation
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