A Novel Approach to Segmentation Using Customer Locations Data and Intelligent Techniques


Öztayşi B. , Gokdere U., Simsek E. N. , Oner C. S.

HANDBOOK OF RESEARCH ON INTELLIGENT TECHNIQUES AND MODELING APPLICATIONS IN MARKETING ANALYTICS, pp.21-39, 2017 (Refereed Journals of Other Institutions) identifier

  • Publication Type: Article / Article
  • Publication Date: 2017
  • Doi Number: 10.4018/978-1-5225-0997-4.ch002
  • Title of Journal : HANDBOOK OF RESEARCH ON INTELLIGENT TECHNIQUES AND MODELING APPLICATIONS IN MARKETING ANALYTICS
  • Page Numbers: pp.21-39

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.