Loss prediction method and device for express cabinet user, equipment and storage medium

Abstract

The invention discloses a loss prediction method and device for an express cabinet user, equipment and a storage medium, and the method comprises the steps: determining at least one loss behavior associated description data corresponding to a target user according to the express cabinet behavior data of the target user to be predicted; And predicting the loss risk of the target user according to the loss behavior associated description data of the lost user of the express cabinet matched with the target user and the loss behavior associated description data corresponding to the target user. Inthe embodiment of the invention, Express cabinet behavior data of a target user are obtained; Loss behavior association description data of the target user is obtained. According to the invention, the loss risk of the user is detected, and the loss behavior association description data of the lost user is combined, so that the monitoring and early warning of the user with the loss risk are realized, the timely response to the potential risk by the operator is facilitated, the operation loss caused by the loss of the express cabinet user is avoided, and the stability of the express cabinet user group is ensured.

Description

technical field [0001] The embodiments of the present invention relate to the field of logistics technology, and in particular, to a method, device, equipment, and storage medium for predicting loss of express cabinet users. Background technique [0002] With the continuous advancement of computer technology and logistics technology, express cabinets have begun to appear in people's vision, and the utilization rate of express cabinets by users directly determines the development prospects of the express cabinet industry. Once a large number of users are lost, the utilization rate of cabinet machines will be low and invalid The emergence of a large number of cabinet machines will greatly affect the development of the entire express cabinet industry. [0003] In the existing technology, there is no effective monitoring method for the loss of express cabinet users. Generally, it is through manual on-site judgment, or by visiting, calling or sending emails to communicate with us...

AI Technical Summary

Problems solved by technology

[0003] In the existing technology, there is no effective monitoring method for the loss of express cabinet users, usually through manual on-site judgment, or through visits, phone calls or emails, etc. Communicate with users to understand the reasons for user churn, so as to improve themselves to avoid a wider range of user churn

[0004]However, such a monitoring method is inefficient and requires a large number of customer service personnel to communicate. At the same time, it can only find out the reasons after the loss of users. churn, it is too late to take recovery measures, and it cannot really predict and prevent user churn

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