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Criterion
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration for Causal Factor Analysis.
Operations
Causal Factor Analysis
Paper illustration for Root Cause Analysis.
Operations
Root Cause 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.For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events.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.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
MediumHighMediumHigh
Timedifferent
1-3 h2-6 h1-4 h1-4 Wochen
Participantsdifferent
1-53-103-81-6
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesEvent Timeline, Causal Factor Chart, Cause List, Corrective ActionsProblem Statement, Cause Hypotheses, Confirmed Causes, Action PlanExperiment results, Decision log, Learning summary
Tagsno overlap
AnalyticsConversionGrowth
CausalityIncidentRoot causeTimeline
Root causeProblem solvingQualityIncident
ExperimentsGrowthAnalyticsValidation
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