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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of HEART Framework with its method-specific working model.
UX Research
HEART Framework
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Purposedifferent
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.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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.
Complexitydifferent
HighMediumMediumMedium
Timedifferent
1-4 Wochen120 min initial, dann laufend1-2 Wochen pro Iteration45-60 min
Participantsdifferent
1-63-62-62-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryHEART-GSM Table, DashboardPrioritized Assumption List, Test Plan, Results ReportAssumption map, Test backlog, Risk ranking
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
MetricsUX researchMeasurementSatisfaction
ExperimentsValidationDiscoveryAssumptions
AssumptionsRiskExperimentsValidation
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