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Criterion
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration of Counter Metrics with its method-specific working model.
Product Strategy
Counter Metrics
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.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
MediumLowLowHigh
Timedifferent
1-2 Wochen30-60 min1-5 Tage1-4 Wochen
Participantsdifferent
1-62-6Nutzertraffic1-6
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncAsync
Outputdifferent
Experiment card, Result summary, Next betCounter Metric List, Guardrail DefinitionsInterest Metrics, Conversion Signal, Learning NoteExperiment results, Decision log, Learning summary
Tags1 shared
MarketingGrowthExperimentsLearning
MetricsMeasurementStrategyExperiments
ValidationExperimentsDemandGrowth
ExperimentsGrowthAnalyticsValidation
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