Research And Application Of Customer Churn

With the development of economy,the competition among enterprises is becoming more and more intense,and customers become the key to improve the competitiveness of enterprises.In the early stage of business development,new customers are crucial for enterprises,but as enterprises develop,the development of new customers is faced with the characteristics of difficulty,high cost and low return,while old customers have the characteristics of low retention cost,high loyalty and high return.In this situation,how to identify customers with the tendency to churn and the reasons for it has become one of the most important concerns of enterprises and has important research significance in various industries.In this paper,we firstly sort out the current status of domestic and international research on customer churn,then,outline the theory of customer churn and related model theory,analyze the factors that lead to customer churn using visualization,correlation,and importance of features,get the key factors that lead to customer churn,and then use logistic regression model,XGBoost model,GBDT model,Tab Net model to establish several The results of the models are evaluated and compared using several indicators such as ROC curve,Precision,Recall,etc.Finally,counterfactual explanations are introduced to explain the results of the models and explore the important factors that affect customer churn.The conclusions obtained in this paper are that the key factors that lead to customer churn are the age of customers,the activity of customers,and the number of products held by customers.Among the established customer churn early warning models,the XGBoost model is optimal in all aspects with an AUC value of 85.1%,an accuracy of 86.9% on the test set,a Precision of 82.57%,a Recall of 71.75%,and an F1 Score of 75.25%.By counterfactual interpretation,it is obtained that,an increase in age leads to an increase in the probability of customer churn,an increase in the number of products held by the customer and the activity of the customer makes the churn less likely,and changes in other factors have little effect on the probability of customer churn.The innovation of this paper lies in the first application of Tab Net model to the development of customer churn early warning model and the use of counterfactual explanation method to analyze the causes of customer churn.