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Criterion
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
A hypothetical failure makes concrete risks, signals, and fitting mitigations visible.
Decision Making
Pre-Mortem
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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.In early initiatives with many uncertainties, planning quickly turns too optimistic. A pre-mortem makes the expected failure visible in advance and sharpens the view of causes, gaps, and countermeasures.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 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
MediumLowMediumHigh
Timedifferent
Multiple workshops over several weeks20–45 min1-3 h1-4 Wochen
Participantsdifferent
2-8Small cross-functional group1-51-6
Formatdifferent
Workshop + asyncWorkshopAsyncAsync
Outputdifferent
Hooked loop, Trigger map, Reward design, Ethics checkRisk list, Mitigation plan, Assumption logFunnel report, Drop-off analysis, Optimization hypothesesExperiment results, Decision log, Learning summary
Tagsno overlap
GrowthBehaviorRetention
RiskDecisionFailurePlanning
AnalyticsConversionGrowth
ExperimentsGrowthAnalyticsValidation
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