Research On Precise Marketing Strategy Of Mobile Banking Based On Data Mining

With the rapid rise of the e-commerce industry,the e-commerce giants,led by Tencent and Alibaba,have directed their spearheads to the financial field.In order to resist the huge impact of Internet finance,commercial banks began to build their own e-commerce platform.In the background of the development of Internet technology,WeChat,Alipay and other mobile phone APP has become an indispensable tool for daily life.For commercial banks,mobile banking has been widely promoted due to its characteristics of convenience and portable nature.It has a large customer base,which enables commercial banks to break the shackles of traditional physical bank branches and has become the main business channels of commercial banks.After years of investment in mobile banking,commercial banks have accumulated lots of user information of mobile banking,which brings great challenges to data processing of commercial banks.Therefore,using advanced data mining technology to process data mining of mobile banking customers has become a necessary step for commercial banks to achieve meticulous management.Commercial banks must abandon the traditional product-centric business philosophy,abandon the extensive marketing model,and be close to the concept of precision marketing.Mining Based on data of mobile banking clients can describe the characteristics of customers more vividly,show the value of customers more clearly.According to the different needs of customers,customer segmentation,market positioning and marketing plan of differentiation can help commercial banks accelerate the strategic transformation,reduce the cost and achieve precision marketing.Based on the modern marketing concept,this paper introduces the concept and characteristics of precision marketing,and expounds the importance of customer segmentation and market positioning in precision marketing.Then,this paper introduces the concept and method of data mining,and proposes that mobile banking data mining has a good match with precision marketing.By comparing traditional marketing,precision marketing based on data mining has a great advantage.In view of this situation,this paper constructs a precise marketing system for commercial banks based on data mining of mobile banking,and discusses the construction principles and implementation process of the system.Then,this paper carries out case analysis on the marketing actuality by taking Wuxi Rural Commercial Bank as example,and puts forward the defects of the existing marketing strategy based on the construction of the system.In order to improve marketing strategy,based on the above precise marketing system,this paper extracts and collates the customer data of mobile banking,and builds data mining model based on data mining method of clustering analysis.According to the results of clustering,this paper analyzes the customer characteristics,and carries out customer segmentation and market positioning,and makes a differentiated marketing strategy.Finally,this paper summarizes the conclusions of the study,and puts forward suggestions for the shortcomings of the paper.The main contributions of this article include the following.First of all,this paper takes mobile banking marketing as a cut-in point,which is not only the marketing of mobile banking business,but also the integrated marketing of commercial banks based on data mining results.Secondly,this paper selects the real data of mobile banking database in Wuxi Rural Commercial Bank,so that the results of data mining are more authentic and reliable.Thirdly,this paper constructs the precision marketing system of mobile phone banking based on data mining.The application of the system can solve problems of Wuxi rural commercial bank effectively,which is facing that the target market needs to be deepened,customer characteristics needs to be excavated and the purpose of marketing needs be improved.At the same time,we hope that this research can provide reference to other commercial banks in the application of precision marketing based on data mining.