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Criterion
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration for Current Reality Tree
Systems Thinking
Current Reality Tree
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Causal Factor Analysis.
Operations
Causal Factor Analysis
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.A Current Reality Tree condenses many symptoms into a few causal chains. The method makes visible which core problems drive several negative effects at once.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.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.
Complexitydifferent
MediumHighHighHigh
Timedifferent
1-3 h2-6 h1-4 Wochen2-6 h
Participantsdifferent
1-53-81-63-10
Formatdifferent
AsyncWorkshopAsyncWorkshop + async
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesCurrent Reality Tree, Core Problems, Intervention IdeasExperiment results, Decision log, Learning summaryEvent Timeline, Causal Factor Chart, Cause List, Corrective Actions
Tagsno overlap
AnalyticsConversionGrowth
Systems thinkingRoot causeConstraintsCausality
ExperimentsGrowthAnalyticsValidation
CausalityIncidentRoot causeTimeline
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