Research on a Customer Churn Combination Prediction Model Based on Decision Tree and Neural Network

Customer churn is a prominent issue facing companies. Preventing customer churn, trying to retain and retain customers has become an important issue for business operations and development. Most of the current customer churn predictions use a single prediction model, which makes it difficult to accurately predict customer churn. Based on the prediction results and confidence of decision tree and neural network model, this paper designs a combined prediction model of customer churn and conducts empirical research on the effectiveness of the model. The prediction results show that compared with the single customer churn prediction model, the combined prediction model has higher accuracy and better prediction effect, and can more intuitively display the basic characteristics of the churn customers.