Title: Research on financial advertisement personalised recommendation method based on customer segmentation
Authors: Liming Wang; Yanni Liu; Jicheng Wu
Addresses: Hangzhou College of Commerce, Zhejiang Gongshang University, No. 18, Xuezheng Str., Xiasha University Town, Hangzhou, China ' School of Management and E-Business, Zhejiang Gongshang University, No. 18, Xuezheng Str., Xiasha University Town, Hangzhou, China ' Hangzhou Sunyard Digital Technology Co. Ltd., No. 3888 Jiangnan Road, Hangzhou, China
Abstract: In the context of mobile internet, financial companies have encountered some obstacles in the development of marketing. The traditional recommendation system based on association rules regards all customers as a whole to carry out the correlation analysis without considering the individual differences, which greatly reduces the effectiveness of personalised recommendation in rule mining stage. Given those shortcomings, this paper proposes a financial product advertising marketing system based on customer segmentation. Through the segmentation of financial customer groups, the method becomes more representative of different consumption habits and consumer characteristics of the customer groups. Then we carry out the association rules mining in various customer groups, and establish the customer base to provide targeted customer personalised service.
Keywords: customer segmentation; data mining; customer segmentation; personalised recommendation.
International Journal of Wireless and Mobile Computing, 2018 Vol.14 No.1, pp.97 - 101
Available online: 13 Feb 2018 *Full-text access for editors Access for subscribers Free access Comment on this article