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Criterion
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
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.The Hooked Model helps clarify engagement loops, user behavior, and experiments. It makes repeat behavior measurable and captures the result as a hooked loop, trigger map, and reward design.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.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 hMultiple workshops over several weeks30-90 min1-4 Wochen
Participantsdifferent
1-52-81-61-6
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesHooked loop, Trigger map, Reward design, Ethics checkDecision Tree, Option Map, Assumption ListExperiment results, Decision log, Learning summary
Tagsno overlap
AnalyticsConversionGrowth
GrowthBehaviorRetention
DecisionTreeOptions
ExperimentsGrowthAnalyticsValidation
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