A model for the mobile market based on customers profile to analyze the churning process
In the current telecommunications market that is reaching high saturation levels, mobile network operators (MNOs) try to position themselves among customers through aggressive marketing campaigns and offers. In this environment where customers have multiple MNOs to choose from, different factors inf...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/90711 |
| Acceso en línea: | https://hdl.handle.net/2117/90711 https://dx.doi.org/10.1007/s11276-016-1334-8 |
| Access Level: | acceso abierto |
| Palabra clave: | Wireless LANs Customer profile Wireless network Churnmo del simulator Xarxes locals sense fil Wi-Fi Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors |
| Sumario: | In the current telecommunications market that is reaching high saturation levels, mobile network operators (MNOs) try to position themselves among customers through aggressive marketing campaigns and offers. In this environment where customers have multiple MNOs to choose from, different factors influence customers’ decisions. In addition to this, mobile number portability contributes to a phenomenon called churning where customers migrate from one MNO to another. Churning impacts not only the network design but also the pricing methods adopted by MNOs, and hence their revenue. It is because of this that MNOs try to reduce churn through retention campaigns. The key factor for the success of these campaigns is to detect potential churners before they leave the service. The state of the art has focused on proposing methods to identify churners based on data mining techniques, however these techniques doesn’t always offer clear explanations for churn reasons. Instead, we use a technique called agent-based modeling to model customers in the mobile telecommunication market and assess the effects of customers characteristics and behaviors on such market. We propose a model that includes some relevant demographic and psychographic characteristics and the utilizations of usage profiles to describe customers. We show with simple experiments how different factors lead to churn in different ways. We believe the proposed approach is useful because MNOs can use it for explanatory, exploratory and predictive purposes. |
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