ATTRITION PREDICTING AND MITIGATING
    3.
    发明公开

    公开(公告)号:US20240289643A1

    公开(公告)日:2024-08-29

    申请号:US18115624

    申请日:2023-02-28

    CPC classification number: G06N5/022

    Abstract: An enterprise's data source relevant to their customers is obtained at predefined intervals of time. The data is processed through classification machine learning models (MLMs) and labeled with features. The labeled data is provided as input to an attrition predicting MLM and one or more lists are provided as output identifying customers likely to leave the enterprise and customers with a high likelihood of remaining with the enterprise when provided an incentive to do so. The one or more lists are provided to enterprise interfaces and/or promotion systems for mitigating customer attrition. In an embodiment, results for the attrition predicting MLM are compared against results predicted by a Recency, Frequency, Monetary (RFM) analyzer in view of subsequent actual observed results for the customers with the enterprise. A continuous feedback loop for retaining the attrition prediction MLM is processed based on the comparison to improve the prediction MLM's F1 accuracy metric.

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