Data-driven Research On Telecom Customer Value Segmentation And Precision Marketing

As the penetration rate of mobile networks is difficult to increase,the growth rate of telecom operators’ business revenue has dropped significantly.The policy risks and competition from Internet companies have also greatly affected the profitability of operators’ existing businesses.Therefore,it is an inevitable trend to drive business operations through data,tap the customer needs behind consumer behavior,and optimize marketing models and product recommendation methods.Based on the current dilemma faced by operators,building a customer value evaluation system that helps optimize marketing services,segment customers based on this,and formulate specific business recommendation strategies are the key points for current telecom operators to use data to drive business.However,the research on customer value,customer segmentation and business recommendation is relatively scattered and has not been well integrated.Appropriate customer value assessment method in light of the current development of telecommunications business,and develops a comprehensive and feasible customer value assessment index system.Secondly,after establishing a complete value evaluation index system,this paper uses the rough set algorithm to determine the weight of each index based on the customer’s historical behavior data,and uses this weight to establish a clustering model for customer segmentation.Finally,this paper uses the reduced indicators obtained by the rough set algorithm to build an XGBoost recommendation model to help operators conduct accurate marketing.Through empirical case analysis,it is found that the customer value evaluation system established in this paper can effectively divide telecommunications customers and determine customer value.At the same time,the rough set algorithm can greatly improve model efficiency while ensuring model accuracy,and solves the problem of processing high-dimensional massive data.Based on the results of rough set model,XGBoost model and logistics model,this paper analyzes customer behaviors in depth,and finds that the customer’s consumption amount,consumption behavior,and its own attributes all affect its choice of package products.Among them,the consumption amount and customer churn probability have the largest impact and recent data is more valuable than historical data.Therefore,this article proposes management suggestions: operators should refine the package products with unlimited traffic to attract more users,set prices reasonably,avoid vicious price competition,combine effective promotion channels and means to optimize marketing,and abandon low-value customers.