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