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.

DOI: 10.1504/IJWMC.2018.090005

International Journal of Wireless and Mobile Computing, 2018 Vol.14 No.1, pp.97 - 101

Received: 28 Dec 2016
Accepted: 29 Oct 2017
Published online: 26 Feb 2018 *

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