Urban mining for direct geomarketing: mobile data analysis with association rules

Maciej Sacharczuk and Katarzyna Kopczewska

Chapter 14 in Handbook on Big Data, Artificial Intelligence and Cities, 2025, pp 277-308 from Edward Elgar Publishing

Abstract: Abstract: Mobility data derived from mobile phones is a valuable source of information for direct geomarketing. By conducting cross-analysis of geolocation and customer trajectories, along with the inclusion of points-of-interest (POI) data on maps, it is possible to gain insights into the specific places customers visit. This knowledge can be utilized to profile the customer base and effectively target customers with tailored advertising content. However, conducting such analyses requires the application of appropriate quantitative tools to handle big data. This chapter provides a detailed exploration of the application of association rules, also known as market basket analysis, to extract information about the urban mobility habits of customers. By leveraging machine learning tools, hidden relationships, patterns, and behaviors can be discovered. This knowledge can prove instrumental in defining target groups within urban areas, identifying complementary visitation patterns for specific locations, and recognizing popular places among the surveyed group.

Keywords: Human mobility; Machine learning; Mobile data; Customer profiles (search for similar items in EconPapers)
Date: 2025
ISBN: 9781803928043
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