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| Criterion |  Operations Change Analysis |  Growth Funnel Analysis |  Engineering Goal Question Metric |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | For a deviation after a change, the method isolates the influence of the altered condition. It narrows down which differences are relevant and which are just accompanying noise. | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | Helps clarify technical problems, hypotheses, and next steps in concrete terms. It breaks a technical problem into testable parts. The result is captured as a GQM table and metric briefs. | 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 | Medium | High |
Timedifferent | 45-120 min | 1-3 h | 90-180 min | 1-4 Wochen |
Participantsdifferent | 2-6 | 1-5 | 3-6 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop | Async |
Outputdifferent | Change Matrix, Cause Hypotheses, Validation Questions, Action List | Funnel report, Drop-off analysis, Optimization hypotheses | GQM Table, Metric Profiles | Experiment results, Decision log, Learning summary |
Tagsno overlap | ChangeRoot causeTroubleshootingComparison | AnalyticsConversionGrowth | MetricsMeasurementEngineeringAlignment | ExperimentsGrowthAnalyticsValidation |