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| Criterion | ![]() Growth A/B Testing | ![]() Product Discovery Experiment Canvas | ![]() Product Strategy Counter Metrics |
|---|---|---|---|
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 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 a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions. |
Complexitydifferent | High | Low | Low |
Timedifferent | 1-4 Wochen | 30-60 min | 30-60 min |
Participantsdifferent | 1-6 | 1-5 | 2-6 |
Formatdifferent | Async | Workshop + async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Completed Experiment Canvas, Success Metric | Counter Metric List, Guardrail Definitions |
Tags1 shared | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryHypothesis | MetricsMeasurementStrategyExperiments |
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