Research on financial advertisement personalised recommendation method based on customer segmentation
by Liming Wang; Yanni Liu; Jicheng Wu
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 14, No. 1, 2018

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.

Online publication date: Mon, 26-Feb-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Wireless and Mobile Computing (IJWMC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com