Combining visual customer segmentation and response modeling

A1 Journal article (refereed)


Internal Authors/Editors


Publication Details

List of Authors: Zhiyuan Yao, Peter Sarlin, Tomas Eklund, Barbro Back
Publisher: SPRINGER
Publication year: 2014
Journal: Neural Computing and Applications
Journal acronym: NEURAL COMPUT APPL
Volume number: 25
Issue number: 1
Start page: 123
End page: 134
Number of pages: 12
ISSN: 0941-0643


Abstract

Customer relationship management is a central part of Business Intelligence, and sales campaigns are often used for improving customer relationships. This paper uses advanced analytics to explore customer behavior during sales campaigns. We provide a visual, data-driven and efficient framework for customer-segmentation and campaign-response modeling. First, the customers are grouped by purchasing behavior characteristics using a self-organizing map. To this behavioral segmentation model, we link segment-migration patterns using feature plane representations. This enables visual monitoring of the customer base and tracking customer behavior before and during sales campaigns. In addition to the general segment-migration patterns, this method provides the capability to drill down into each segment to visually explore the dynamics. The framework is applied to a department store chain with more than 1 million customers.


Keywords

Business Intelligence, Campaign-response modeling, Customer relationship management (CRM), Customer segmentation, Visual analytics

Last updated on 2019-10-12 at 03:45