Identifying audiences that contribute to metric anomalies
Abstract:
The present disclosure is directed toward systems and methods for identifying contributing audience segments associated with a metric anomaly. One or more embodiments described herein identify contributing factors based on statistical analysis and machine learning. Additionally, one or more embodiments identify audience segments associated with each contributing factor. In one or more embodiments, the systems and methods provide an interactive display that enables a user to select a particular anomaly for further analysis. The interactive display also provides additional interfaces through which the user can view informational displays that illustrate the factors and segments that caused the particular anomaly and how those factors correlate with each other.
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