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| Criterion |  Growth A/B Testing |  Agile Affinity Estimation |  Decision Making Delphi Method |  Agile Bucket System |
|---|---|---|---|---|
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 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 knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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. |
Complexitydifferent | High | Medium | High | Medium |
Timedifferent | 1-4 Wochen | 30-90 min | 1-4 Wochen | 30-90 min |
Participantsdifferent | 1-6 | 3-12 | 6-30 Experten | 3-12 |
Formatdifferent | Async | Workshop | Async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Affinity Size Map, Grouped Estimates, Unclear Items | Expert Forecast, Consensus Range, Assumption Notes | Bucketed Backlog, Relative Estimates, Split Candidates |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | EstimationBacklogRelative sizing | ForecastingExpertsDecisionStrategy | EstimationBacklogRelative sizing |