Customer behavior prediction method and device, equipment and medium

Abstract

The embodiment of the invention provides a customer behavior prediction method and device, equipment and a medium, and the method comprises the steps: obtaining the attributes of a sample customer andthe experience information corresponding to the sample customer from a template, and wherein the experience informationis the experience information of a worker during the maintenance of the sample customer; if the attribute of the sample client or the experience information corresponding to the sample client belongs to fuzzy information, processing the attribute of the sample client and the experience information corresponding to the sample client based on a fuzzy decision tree algorithm to obtain a first decision tree; according to the first decision tree, predicting the behavior of a target customer, wherein the sample customer and the target customer are customers of a communication operator respectively. According to the embodiment of the invention, the method achieves the automaticand intelligent provision of customer retention and loss prediction data for a worker, assists the worker to carry out the targeted customer retention, and reduces the risk of customer loss.

Description

technical field [0001] The present invention relates to the technical field of communications, and in particular to a customer behavior prediction method, device, equipment and medium. Background technique [0002] At present, the competition among communication operators is becoming increasingly fierce, and the rate of customer churn continues to rise. When the communication market share has reached saturation, the cost of developing new customers is much higher than the cost of maintaining old customers. Therefore, it is the top priority to retain existing customers and reduce the rate of customer churn. In order to reduce the loss of old customers, it is necessary to predict the tendency of customers to leave the network in advance, and actively take customer care in a targeted manner to retain customers in a timely manner. [0003] Most of the existing methods are based on the establishment of customer retention systems and core customer retention and other topics. Thes...

AI Technical Summary

Problems solved by technology

However, this method is too dependent on the setting of the index range, and requires the account manager to actively explore potential high-churn risk customers. The initiative requirements for account managers are relatively high, and it is impossible to realize automatic and intelligent prediction of high-churn risk customers.

Images