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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Causal Factor Analysis.
Operations
Causal Factor Analysis
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
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.For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events.Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it.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
HighHighLowLow
Timedifferent
1-4 Wochen2-6 h45-90 min30-60 min
Participantsdifferent
1-63-102-81-5
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryEvent Timeline, Causal Factor Chart, Cause List, Corrective ActionsAssumption List, Critical Assumptions, Learning PlanCompleted Experiment Canvas, Success Metric
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
CausalityIncidentRoot causeTimeline
AssumptionsRiskDecisionDiscovery
ExperimentsValidationDiscoveryHypothesis
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