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Criterion
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan.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.When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.
Complexitydifferent
MediumMediumHighMedium
Timedifferent
Multiple workshops over several weeks45-75 min1-4 Wochen1-5 Tage
Participantsdifferent
2-82-81-6Nutzertraffic
Formatdifferent
Workshop + asyncWorkshopAsyncAsync
Outputdifferent
Hooked loop, Trigger map, Reward design, Ethics checkTest Matrix, Test PlanExperiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning Decision
Tagsno overlap
GrowthBehaviorRetention
ExperimentsValidationDiscoveryOptions
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
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