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Criterion
Paper illustration of HEART Framework with its method-specific working model.
UX Research
HEART Framework
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.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
120 min initial, dann laufend1-2 Wochen30-60 min1-4 Wochen
Participantsdifferent
3-61-61-51-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
HEART-GSM Table, DashboardExperiment card, Result summary, Next betCompleted Experiment Canvas, Success MetricExperiment results, Decision log, Learning summary
Tagsno overlap
MetricsUX researchMeasurementSatisfaction
MarketingGrowthExperimentsLearning
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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