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Criterion
Paper illustration of HEART Framework with its method-specific working model.
UX Research
HEART Framework
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
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
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 many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses.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
120 min initial, dann laufend1-3 h30-60 min1-4 Wochen
Participantsdifferent
3-61-52-61-6
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
HEART-GSM Table, DashboardFunnel report, Drop-off analysis, Optimization hypothesesCounter Metric List, Guardrail DefinitionsExperiment results, Decision log, Learning summary
Tagsno overlap
MetricsUX researchMeasurementSatisfaction
AnalyticsConversionGrowth
MetricsMeasurementStrategyExperiments
ExperimentsGrowthAnalyticsValidation
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