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Improving the Predictive Power of Business Performance Measurement Systems by Constructed Data Quality Features? Five Cases Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Retail Store Segmentation for Target Marketing

Authors : Emrah Bilgic, Mehmed Kantardzic, Ozgur Cakir

Published in: Advances in Data Mining: Applications and Theoretical Aspects

Publisher: Springer International Publishing

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Abstract

In this paper, we use Data Mining techniques such as clustering and association rules, for the purpose of target marketing strategy. Our goal is to develop a methodology for retailers on how to segment their stores based on multiple data sources and how to create marketing strategies for each segment rather than mass marketing. We have analyzed a supermarket chain company, which has 73 stores located in the Istanbul area in Turkey. First, stores are segmented in 5 clusters using a hierarchical clustering method and then association rules are applied for each cluster.

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previous chapter How to Support Customer Segmentation with Useful Cluster Descriptions
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Appendix
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Metadata
Title
Retail Store Segmentation for Target Marketing
Authors
Emrah Bilgic
Mehmed Kantardzic
Ozgur Cakir
Copyright Year
2015
Book
Advances in Data Mining: Applications and Theoretical Aspects

Print ISBN: 978-3-319-20909-8

Electronic ISBN: 978-3-319-20910-4

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-20910-4_3

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