Cart (Loading....) | Create Account
Close category search window
 

A Knowledge Discovery Based Customization Services Model and Empirical Analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Guoling Lao ; Shanghai Univ. of Finance & Econ., Shanghai ; Zhaohui Zhang

It is not feasible and practical to offer "one to one" customer service to every customer. Customer segmentation is needed urgently before drawing customization service strategy. Most stockjobbers in China classify their customers into three main groups: big customer, secondary customer, ordinary customer, according to the customers' possessions they declared. But this classification approach is not reasonable and effective enough, as not all wealthy customers bring high contribution value to the stockjobber while some customers who do not have a high level of investment capital account for large amounts of stockjobber's profits. This article shed lights on the common characteristics of the high-valued customer. After analyzing the classical CLV model, we find that customer potential contribution value to the stockjobbers largely depends on some key factors. At the basis of this, whether a new customer has high contribution value to the stockjobber in the future can be accurately predicted in their entering phase. The result of the empirical study validated this and it also reveals that it's possible and reasonable to differentiate high CPV customer and low CPV ones through quantitative analysis.

Published in:

Service Systems and Service Management, 2007 International Conference on

Date of Conference:

9-11 June 2007

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.