Design And Implementation Of CRM System In Insurance Enterprises Based On Cluster Analysis Algorithms

As the degree of automation and level of informationization of business management continues to develop and the business management concepts keeps updating,the traditional method of insurance customer relationship management has been unable to meet the basic needs of the modern insurance company.Meanwhile,the data mining techniques are becoming increasingly sophisticated,allowing the use of data mining technology to further analyze the insurance customer information so as to transform customer information into customer knowledge and ultimately to provide support for corporate decision-making for expanding market share.Combined with the company’s experience data,the decision tree and other data mining methods,this thesis studies a branch of PICC.It has designed and developed CRM system applied to the insurance company.Based on the life cycle theory and on the features of customer relationship management,and with an understanding of the business demands of CRM system operating for insurance companies,this thesis paper has organized the systematic demands of CRM system and developed such a system responding to the business demands.This system includes four parts: market management module,sales module,customer management module and customer service module.In the design of these modules,the thesis uses decision tree data preprocessing techniques and other data mining technology,with a focus on the process of its generation.Practice has proved that the CRM system of the PICC provides scientific and effective methods for customer relationship management,which improves their market competitiveness.