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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of RAID Log with a method-specific labelled workspace.
Delivery
RAID Log
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
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 scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as a RAID Log and a source for status reporting.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.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.
Complexitydifferent
HighLowMediumLow
Timedifferent
1-4 Wochen30 min Setup, dann laufend45-60 min30-60 min
Participantsdifferent
1-61-3 maintaining, briefing for everyone2-81-5
Formatdifferent
AsyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryRAID Log, Status Report SourceAssumption map, Test backlog, Risk rankingCompleted Experiment Canvas, Success Metric
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
RiskTrackingStakeholdersGovernance
AssumptionsRiskExperimentsValidation
ExperimentsValidationDiscoveryHypothesis
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