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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
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 knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together.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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.
Complexitydifferent
HighHighLowMedium
Timedifferent
1-4 Wochen1-4 Wochen1-2 h1-2 Wochen pro Iteration
Participantsdifferent
1-66-30 Experten2-82-6
Formatdifferent
AsyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryExpert Forecast, Consensus Range, Assumption NotesDIBB document, Belief list, Bet list, Learning reportPrioritized Assumption List, Test Plan, Results Report
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ForecastingExpertsDecisionStrategy
StrategyDecisionAssumptionsHypothesis
ExperimentsValidationDiscoveryAssumptions
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