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Criterion
Paper illustration of Lean UX Canvas with its method-specific working model.
UX Design
Lean UX Canvas
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
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
The Lean UX Canvas helps clarify user behavior, touchpoints, and concept decisions. It makes assumptions and desired outcomes visible and captures the result as a completed canvas, hypothesis list, and first experiment.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.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
MediumMediumLowLow
Timedifferent
2-3 h30-90 min1-2 h30-60 min
Participantsdifferent
3-81-62-81-5
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Completed Lean UX Canvas, Hypothesis list, First experimentDecision Tree, Option Map, Assumption ListDIBB document, Belief list, Bet list, Learning reportCompleted Experiment Canvas, Success Metric
Tagsno overlap
CanvasHypothesisOutcomesDiscovery
DecisionTreeOptions
StrategyDecisionAssumptionsHypothesis
ExperimentsValidationDiscoveryHypothesis
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