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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Context Map workspace showing the question, observations, and next decision.
Domain Modeling
Context Map
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.When several contexts need to talk to each other, it makes their relationships and dependencies legible. It helps sort integration pressure and responsibilities across system boundaries.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
HighMediumLowMedium
Timedifferent
1-4 Wochen1-3 h1-2 h45-60 min
Participantsdifferent
1-62-82-82-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryContext Map, Integration Patterns, Boundary NotesDIBB document, Belief list, Bet list, Learning reportAssumption map, Test backlog, Risk ranking
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
Domain-Driven DesignBoundariesStrategy
StrategyDecisionAssumptionsHypothesis
AssumptionsRiskExperimentsValidation
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