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| Criterion | ![]() Growth A/B Testing | ![]() Operations Causal Factor Analysis | ![]() Operations Root Cause Analysis | ![]() Product Discovery Smoke Test |
|---|---|---|---|---|
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. | For an event with a complicated course, the method breaks down the contributing factors along the timeline. It shows how conditions, decisions, and reactions together produce a course of events. | When a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another. | 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. |
Complexitydifferent | High | High | Medium | Low |
Timedifferent | 1-4 Wochen | 2-6 h | 1-4 h | 1-5 Tage |
Participantsdifferent | 1-6 | 3-10 | 3-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Event Timeline, Causal Factor Chart, Cause List, Corrective Actions | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | CausalityIncidentRoot causeTimeline | Root causeProblem solvingQualityIncident | ValidationExperimentsDemandGrowth |



