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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Leverage Points with its method-specific working model.
Systems Thinking
Leverage Points
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
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.Leverage Points show exactly where interventions in a system produce a disproportionate effect. It draws relationships, patterns, and feedback loops. The result is captured as a leverage map and action strategy.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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.
Complexitydifferent
HighHighLowMedium
Timedifferent
1-4 WochenHalf day1-2 h45-60 min
Participantsdifferent
1-63-122-82-8
Formatdifferent
AsyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryLeverage Map, Action StrategyDIBB document, Belief list, Bet list, Learning reportAssumption map, Test backlog, Risk ranking
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
Systems thinkingChangeStrategy
StrategyDecisionAssumptionsHypothesis
AssumptionsRiskExperimentsValidation
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