The Research On The Customer Churn Prediction Of Online Shopping

The customer churn is a common phenomenon in the business management,the cost to attract new customers is actually much higher than retaining the old customers.If the enterprise only focus on attracting new customers,ignoring the loss of old customers management,it will lead to the number of customers is stable,while the profitability is declining.In the modern enterprise management,strengthening the customer care and reducing the customer churn can enhance the competitiveness of enterprises,so customer churn management become an important issue in many industries.In recent years,the e-commerce industry has developed rapidly while facing increasingly prominent problems.The binding on the customer is weak,resulting the customer churn rate is much higher than the relationship between the telecommunications,banking and other industries.Based on the existing research on the customer churn,this paper focuses on the churn of online shopping.Through the analysis of the loss of online shopping customers,it is helpful for e-commerce enterprises to discover the customers with loss tendency in time,do the pre-control work for the customer churn management,thereby effectively reducing the churn rate.The main research work of this paper is as follows: Firstly,this paper mainly elaborates the theory of customer churn management,data mining and the application of data mining technology in customer churn prediction.Secondly,taking the electronic products of a B2 C e-commerce website as an example,finishing the actual transaction data of online shopping customers,using the BP neural network and the support vector machine model to predict the customer's churn,Then,in order to improve the accuracy of customer churn prediction,on the basis of the single forecasting model,using the combination forecasting model to classify the customer churn.The empirical results show the combined forecasting model obviously improved the recall rate,coverage rate and lift degree.Finally,using the theory of RFM to analyze the value of the churn customers to understand the situation of different customer,combined with the life cycle of online shopping customers to summarize the reasons of the customer,at the same time put forward the customer retention strategy.