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Criterion
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration for Root Cause Analysis.
Operations
Root Cause Analysis
Paper illustration for Root Cause Tree Analysis
Operations
Root Cause Tree Analysis
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.When a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another.For a problem with several suspected causes, the method builds a causal structure instead of a mere list. It makes visible how causes connect and where the strongest points of leverage lie.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 h1-4 h1-3 h1-4 Wochen
Participantsdifferent
1-53-82-81-6
Formatdifferent
AsyncWorkshop + asyncWorkshopAsync
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesProblem Statement, Cause Hypotheses, Confirmed Causes, Action PlanCause Tree, Evidence Notes, CountermeasuresExperiment results, Decision log, Learning summary
Tagsno overlap
AnalyticsConversionGrowth
Root causeProblem solvingQualityIncident
Root causeTreeIncidentQuality
ExperimentsGrowthAnalyticsValidation
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