Research On Data Analysis Of Commercial Bank Based On CRM System

After the reform and opening up,because of China's rapid economic development,increasingly fierce market competition,the focus of the competition is also constantly changing,from the previous product competition gradually transformed into customer-centric service competition.Customer-centric service competition is the key point to deal with the relationship between enterprise and customer management.Customer relationship management is particularly important for that commercial bank provide a wide variety of financial services to the masses as a service industry.In the era of big data,customer information data has an explosive growth trend,in the face of an unprecedented huge amount of data,the accuracy and reliability of date could only reflect by deeper level of data mining.Therefore,it is necessary for commercial banks to carry out big data analysis on the customer relationship management system.Through the deep mining and comprehensive analysis of the large amount of customer information,commercial banks can truly understand the customer's individual behavior and demand.Different customershave different value for the bank.The work of this paper is to analyze the development path of commercial banks in the big data era,establish a customer relationship management system for commercial banks,and mainly introduces the classification of customers in the customer relationship management system.The MapReduce clustering method is used to classify the customers successfully.I am engaged in the financial industry,the commercial bank is responsible for the management of high-end customers.In the ever-changing environment,customer demand is also changing: from the basis of deposit and loan,settlement business to the current wealth management,wealth preservation,heritage planning.How to understand the customer,identify customer needs,providing personalized customized products and services;how to use data analysis to obtain customer value goals to achieve precision marketing,improve management efficiency;these are worthy of study and discussion.