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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of a two-by-two Ansoff Matrix with four growth directions
Business Strategy
Ansoff Matrix
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
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.The Ansoff Matrix organizes growth options by market and product relation. It helps weigh expansion, diversification, and adaptation cleanly against each other.DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report.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
HighLowLowLow
Timedifferent
1-4 Wochen45-90 min1-2 h30-60 min
Participantsdifferent
1-62-82-81-5
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryAnsoff Matrix, Growth Options, Risk NotesDIBB document, Belief list, Bet list, Learning reportCompleted Experiment Canvas, Success Metric
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
GrowthStrategyMarketPortfolio
StrategyDecisionAssumptionsHypothesis
ExperimentsValidationDiscoveryHypothesis
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