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Criterion
Paper illustration for Flywheel.
Growth
Flywheel
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth.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.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 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.
Complexitydifferent
MediumMediumLowHigh
Timedifferent
60-120 min1-2 Wochen pro Iteration1-2 h1-4 Wochen
Participantsdifferent
3-82-62-81-6
Formatdifferent
WorkshopWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Flywheel Map, Friction Points, Growth Levers, Experiment BacklogPrioritized Assumption List, Test Plan, Results ReportDIBB document, Belief list, Bet list, Learning reportExperiment results, Decision log, Learning summary
Tagsno overlap
GrowthRetentionConversion
ExperimentsValidationDiscoveryAssumptions
StrategyDecisionAssumptionsHypothesis
ExperimentsGrowthAnalyticsValidation
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