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| Criterion |  Agile Affinity Estimation |  Agile Bucket System |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
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 a large batch of work needs a fast, rough estimate, it sorts items into predefined size buckets. It sorts work by value, risk, and delivery ability. The result is captured as a Bucketed Backlog, Relative Estimates, and Split Candidates. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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. |
Complexitydifferent | Medium | Medium | Low | High |
Timedifferent | 30-90 min | 30-90 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 3-12 | 3-12 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop | Workshop | Async | Async |
Outputdifferent | Affinity Size Map, Grouped Estimates, Unclear Items | Bucketed Backlog, Relative Estimates, Split Candidates | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | EstimationBacklogRelative sizing | EstimationBacklogRelative sizing | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |