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Criterion
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration of a branching impact map with a Why goal at the root, actor circles, How behavior changes and What options.
Product Strategy
Impact Mapping
Paper illustration of Counter Metrics with its method-specific working model.
Product Strategy
Counter Metrics
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.When a goal needs to be connected to several possible paths, it shows chains of impact instead of feature lists. It connects business goal, behavior change, and measures.When a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions.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
MediumMediumLowHigh
Timedifferent
1-2 Wochen45-90 min30-60 min1-4 Wochen
Participantsdifferent
1-63-82-61-6
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncAsync
Outputdifferent
Experiment card, Result summary, Next betImpact Map, Outcome Hypotheses, Delivery OptionsCounter Metric List, Guardrail DefinitionsExperiment results, Decision log, Learning summary
Tagsno overlap
MarketingGrowthExperimentsLearning
OutcomesStrategyBehaviorPlanning
MetricsMeasurementStrategyExperiments
ExperimentsGrowthAnalyticsValidation
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