Credit Card Customer Value Analysis:n Application of Quantile Regression
Date Issued
2009
Date
2009
Author(s)
Yen, Yi-Hsuan
Abstract
Customer Relationship Management（CRM） is a very important issue for companies nowadays to increase customer value and maintain customer loyalty. Though one-to-one marketing is the most ideal method to provide specific product or service for each customer by their heterogeneities, companies are urgent to distinguish the “most valuable customers” efficiently due to the limited resource. Thus, the preferences and needs of “high-valued customers” are the goals needed to be achieved. Consequently, companies can improve their profit and get sustainable growth by maximizing customer’s lifetime value. By database marketing, consumer’s behaviors are exactly the variables of market segmentations. In the mean time, this method could sharp the ability to find out the target market more efficiently. he main purpose of this research is to help companies to establish a better clear understanding of their customers. We use customers’ past consumption data and database marketing analysis techniques to identify each customer more precisely. This research uses quantile regression as the main analysis model to analyze customer value, and 4 variables, including “the total transactions amount”, “the average transactions amount”, “the percentage of each transaction category”, and “the active of each customer” are used to be the dependent variables.
Subjects
Quantile Regression
Customer Value Analysis
Credit Card
Database Marketing
Customer Relationship Management(CRM)
SDGs
Type
thesis