Abstract
Abstract The construction of early warning model of customer churn in e-commerce platform can help e-commerce enterprises in China to strengthen the risk prevention of customer churn, improve efficiency of customer management and resolve the crisis of customer churn. Therefore, this paper analyses the definition basis and evaluation method of customer churn, and clarifies the function and content of early warning customer churn. By using the K-means clustering analysis of sample data, the early warning level of customer churn risk is categorized. By taking the established index system data as the input layer data of neural network, the early warning model of customer churn risk of e-commerce platform based on neural network is constructed. The test results show that the accuracy of the model is 100%, which can provide reference for the early warning research of customer churn risk in the e-commerce industry of China.
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