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Criterion
Paper illustration of a JTBD interview notebook with a decision timeline, forces of change and a concise job hypothesis.
Product Discovery
Jobs to Be Done
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration of Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
Purposedifferent
When switching motives and progress are unclear, it reconstructs the situation from real customer circumstances. It shows why a switch happens and what kind of progress is being sought.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 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.When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog.
Complexitydifferent
MediumHighLowMedium
Timedifferent
1-3 Wochen1-4 Wochen30-60 min60-90 min
Participantsdifferent
5-12 Interviews1-61-53-8
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop
Outputdifferent
Job Stories, Outcome Statements, Opportunity ListExperiment results, Decision log, Learning summaryCompleted Experiment Canvas, Success MetricPrioritization Canvas, Hypothesis Backlog
Tagsno overlap
CustomerOutcomesNeeds
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
ExperimentsPrioritizationDiscoveryHypothesis
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