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Criterion
A paper-based illustration representing North Star Metric with its core stages and visible working result.
Growth
North Star Metric
Paper illustration of Hooked Model with its method-specific working model.
Growth
Hooked Model
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
When product teams track many metrics, the view of the actual customer outcome easily gets lost. A North Star Metric bundles growth, usage, and value contribution into one signal that makes the system's direction visible.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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog.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
1-2 hMultiple workshops over several weeks60-90 min1-4 Wochen
Participantsdifferent
3-82-83-81-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopAsync
Outputdifferent
North Star metric, Input metric tree, Measurement cadenceHooked loop, Trigger map, Reward design, Ethics checkPrioritization Canvas, Hypothesis BacklogExperiment results, Decision log, Learning summary
Tagsno overlap
GrowthMetricsAlignmentRetention
GrowthBehaviorRetention
ExperimentsPrioritizationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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