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Criterion
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration of HEART Framework with its method-specific working model.
UX Research
HEART Framework
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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.Helps clarify observations, needs, and patterns in concrete terms. It groups observations into patterns, questions, and decisions. The result is captured as a HEART-GSM table and dashboard.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 only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
MediumMediumHighLow
Timedifferent
1-2 Wochen120 min initial, dann laufend1-4 Wochen1-5 Tage
Participantsdifferent
1-63-61-6Nutzertraffic
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncAsync
Outputdifferent
Experiment card, Result summary, Next betHEART-GSM Table, DashboardExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
MarketingGrowthExperimentsLearning
MetricsUX researchMeasurementSatisfaction
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
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