Study On Potential Customer Churn Prediction And Customer Retention Strategy Of Mobile S Branch

After the formation of the situation of tripartite confrontation in China's telecommunications industry,operators have been engaged in fierce market competition.The competition for customer resources is a top priority for all communication operators.With the high saturation of the communication market,the quantity and quality of new customers are not as good as before,and the loss of customers has intensified continuously,which causing the growth of business operating income to slow down or even decline.Therefore,improving the existing customer retention rate,predicting and retaining potential customers are increasingly becoming the top priority of all levels of telecommunications companies.However,the loss of most customers,especially the high-end customers,is shown as the form of becoming zero-usage users.Therefore,if the operators can accurately predict the potential zerousage users,they can conduct targeted marketing and complete the effective retention work for customers.Based on customer life cycle,customer value and customer maintenance theory,this paper uses data mining technology to conduct prediction analysis on potential lost customers,and takes the customer churn data of Mobile S Branch as the research object by using the company's data mining tools and Decision Tree C5.0.The algorithm establishes a potential customer churn prediction model.In the modeling process,the customer's active network time,brand tariff,attribution channel and county distribution are fully considered,and the zero-usage users are refined and classified,and the result sets of multiple the zero-usage users are generated and predicted a list of customer churns.Finally,based on the results of the churn prediction model,a potential customer churn retention system is constructed,and the customer retention strategy is proposed according to each stage of the customer's life cycle.The focus is on improving service capability to enhance customer loyalty and on advancing marketing ability to increase customer viscosity.We have targeted a series of customer retention measures for lost customers and achieved good results.The research results of this paper have practical use value for the Mobile S Branch to solve the customer churn problem,and enable to guide the customer churn prediction and retention work of other companies.