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Criterion
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
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.When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together.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
MediumHighMediumHigh
Timedifferent
Multiple workshops over several weeks1-4 Wochen1-3 h1-4 Wochen
Participantsdifferent
2-86-30 Experten1-51-6
Formatdifferent
Workshop + asyncAsyncAsyncAsync
Outputdifferent
Hooked loop, Trigger map, Reward design, Ethics checkExpert Forecast, Consensus Range, Assumption NotesFunnel report, Drop-off analysis, Optimization hypothesesExperiment results, Decision log, Learning summary
Tagsno overlap
GrowthBehaviorRetention
ForecastingExpertsDecisionStrategy
AnalyticsConversionGrowth
ExperimentsGrowthAnalyticsValidation
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