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Criterion
A 5 Whys working surface connects an observable problem with evidenced causes, marked uncertainty and concrete countermeasures with ownership.
Operations
5 Whys
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
For a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description.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 demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.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
LowHighMediumLow
Timedifferent
15-30 min1-4 Wochen1-5 Tage30-60 min
Participantsdifferent
2-61-6Nutzertraffic1-5
Formatdifferent
WorkshopAsyncAsyncWorkshop + async
Outputdifferent
Root cause notes, CountermeasuresExperiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning DecisionCompleted Experiment Canvas, Success Metric
Tagsno overlap
Root causeIncidentLeanProblem solving
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
ExperimentsValidationDiscoveryHypothesis
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