A novel approach to segmentation using customer locations data and intelligent techniques

Başar Öztayşi; Ugur Gokdere; Esra Nur Simsek; Ceren Salkin Oner

doi:10.4018/978-1-5225-0997-4.ch002

A novel approach to segmentation using customer locations data and intelligent techniques

Başar Öztayşi^*, Ugur Gokdere, Esra Nur Simsek, Ceren Salkin Oner

^*Corresponding author for this work

Department of Industrial Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Citation (Scopus)

Abstract

Customer segmentation has been one of hottest topics of marketing efforts. The traditional sources of data used for segmentation are demographics, monetary value of transactions, types of product/service selected. Today, data gathered by location based services can also be used for customer segmentation. In this chapter a real world case study is summarized and the initial segmentation results are presented. As the application, data gathered from beacons sited in 4000 locations and Fuzzy c-means clustering algorithm are used. The steps of the application are as follows: (1) Categorization of the shops, (2) Summarization of the location data, (3) Applying fuzzy clustering technique, (4) Analyzing the results and profiling. Results show that customers' location data can provide a new perspective to customer segmentation.

Original language	English
Title of host publication	Handbook of Research on Intelligent Techniques and Modeling Applications in Marketing Analytics
Publisher	IGI Global
Pages	22-39
Number of pages	18
ISBN (Electronic)	9781522509981
ISBN (Print)	1522509976, 9781522509974
DOIs	https://doi.org/10.4018/978-1-5225-0997-4.ch002
Publication status	Published - 25 Oct 2016

Bibliographical note

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© 2017 by IGI Global. All rights reserved.

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10.4018/978-1-5225-0997-4.ch002

Cite this

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A novel approach to segmentation using customer locations data and intelligent techniques

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