Abstract
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.
Highlights
The recent years has been witnessing a booming growth in the mobile industry fueled by high penetration rate, advancement of smartphone technologies and the availability of, in some cases, indispensable mobile applications addressing wide spectrum of sectors such as entertainment, gaming, business transactions, banking transactions, reservation, Internet and many others
Besides the fact of being inherently wide, the customer base for such markets is heterogeneous in the sense that customers have different service requirements which lead to different usage patterns
This paper aims at providing a case study on customer segmentation in mobile telecommunication markets using Self Organizing Map (SOM) technology
Summary
The recent years has been witnessing a booming growth in the mobile industry fueled by high penetration rate, advancement of smartphone technologies and the availability of, in some cases, indispensable mobile applications addressing wide spectrum of sectors such as entertainment, gaming, business transactions, banking transactions, reservation, Internet and many others. A tool that can be effective in this regard is Kohonen’s Self Organizing Map (SOM) which is a neural-network based approach that maps a multidimensional input space to one or twodimensional space that can be visualized [5] This approach helps perform segmentation while preserving topological relations among the different elements of the space. This paper aims at providing a case study on customer segmentation in mobile telecommunication markets using SOM technology. That cover on-net and off-net calling behavior In this regard, we use SOM to categorize customers according to this set of attributes. We show that data users, while forming the largest segment, have the lowest loyalty rate This counterintuitive result highlights inefficiencies in marketing strategies that can overlook such wide segment.
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