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| Criterion |  Agile Affinity Estimation |  Facilitation Dot Estimation |  Growth A/B Testing |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. | When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets. | 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. |
Complexitydifferent | Medium | Low | High | Low |
Timedifferent | 30-90 min | 5-20 min | 1-4 Wochen | 30-60 min |
Participantsdifferent | 3-12 | 3-20 | 1-6 | 1-5 |
Formatdifferent | Workshop | Workshop | Async | Workshop + async |
Outputdifferent | Affinity Size Map, Grouped Estimates, Unclear Items | Effort Heatmap, Risk Signals, Discussion Targets | Experiment results, Decision log, Learning summary | Completed Experiment Canvas, Success Metric |
Tagsno overlap | EstimationBacklogRelative sizing | EstimationEffortRisk | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryHypothesis |