Mercados

Available online at www.sciencedirect.com

Expert Systems

with Applications

Expert Systems with Applications 34 (2008) 2754–2762

www.elsevier.com/locate/eswa

Intelligent value-based customer segmentation method for campaign management: A case study of automobile retailer

Chu Chai Henry Chan *

E-Business Research Laboratory, Department of Industrial Engineering and Management,Chaoyang University of Technology,

No. 168, Jifong East Road, Wufong Township, Taichung County, Taiwan, ROC

Abstract

Most marketers have difficulty in identifying the right customers to engage in successful campaigns. So far, customer segmentation is a popular method that is used for selecting appropriate customers for a launch campaign. Unfortunately, the link between customerseg-mentation and marketing campaign is missing. Another problem is that database marketers generally use different models to conduct customer segmentation and customer targeting. This study presents a novel approach that combines customer targeting and customer segmentation for campaign strategies. This investigation identifies customer behavior using a recency, frequency and monetary (RFM) model and thenuses a customer life time value (LTV) model to evaluate proposed segmented customers. Additionally, this work proposes using generic algorithm (GA) to select more appropriate customers for each campaign strategy. To demonstrate the efficiency of the proposed method, this work performs an empirical study of a Nissan automobile retailer to segment over 4000 customers. The experimental results demonstratethat the proposed method can more effectively target valuable customers than random selection.
₃ 2007 Published by Elsevier Ltd.

Keywords: Customer segmentation; Generic algorithm; Customer lifetime value; Campaign management

1. Introduction

For a successful business, engaging in an effective cam-paign is a key task for marketers. Traditionally, marketers must first identify marketsegmentation using a mathemat-ical mode and then implement an efficient campaign plan to target profitable customers ( Fraley & Thearting, 1999). This process confronts considerable problems. First, most previous studies used various mathematical models to seg-ment customers without considering the correlation between customer segmentation and a campaign. Previ-ously, the link between customersegmentation and cam-paign activities was most manual or missing ( Fraley & Thearting, 1999). From an academic perspective, the pro-cesses of customer segmentation should consider the con-straints or dependent variables of campaign activities in

* Tel.: +886 423323000x4251; fax: +86 4 23742327. E-mail address: ccchan@cyut.edu.tw

0957-4174/$ - see front matter ₃ 2007 Published byElsevier Ltd. doi:10.1016/j.eswa.2007.05.043

attempting to increase the relevancy of both processes. For marketing researchers, segmentation should not the end in itself, but rather a means to an end ( Jonker, Piersma, & Poel, 2004). Following the notion proposed by Jonker, this work presents a conceptual model by counting the sig-nificant campaign dependent variables of customer target-ing incustomer segmentation. In this way, the processes of customer segmentation and targeting thus can be linked and solved together. The outcomes of customer segmenta-tion of this study are more meaningful and useful for mar-keters than the others.

Second, in most previous studies, the quality of a segmen-tation methodology is measured based on within-segment and inter-segment heterogeneity ( Wedel& Kamakura, 2000). Realistically, marketers are concerned with and inter-ested in maximizing the net value of targeted customers, rather than caring about within-segment homogeneity or targeting rate ( Jonker et al., 2004; Kim, Street, Russell, & Menczer, 2005). To solve the core problem of marketers facing, this investigation applies a customer life time value

C.C.H. Chan / Expert...