Classification of Mobile Customers Behavior and Usage Patterns using Self-Organizing Neural Networks

Rawan Ghnemat, Edward Jaser


Mobile usage is witnessing a booming growth attributed to advances in smartphone technologies, the extremely high penetration rate and the availability of popular mobile applications. Telecommunication markets have been injecting huge investments to fulfil the sheer demand on wireless network and mobile services as a result. Such potentials highlights the importance of behavioral segmentation of mobile network users to target different sectors of customers with efficient marketing strategies and ensure customer retention in light of the intense competition. A major hurdle in applying this approach is the number of dimensions underlying customer preferences which makes it hard to visualize similarities among customers and formulate behavioral segments correctly and efficiently. In this paper, we use self-organizing maps, to detect different usage patterns of mobile users. The proposed system is tested using a large sample of customers’ data provided by major mobile operator in Jordan. The study detected different behavioural segments in this market and highlights the role of data users in modern mobile markets. In this context, we give detailed analysis of our results on user behavioral segmentation.


Mobile telecommunications; Self-Organizing Map; Customer segmentation

Full Text:


International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923
Creative Commons License
Scopus logo IET Inspec logo DBLP logo EBSCO logo Ulrich's logo MAS logo