International Journal of
Physical Sciences

  • Abbreviation: Int. J. Phys. Sci.
  • Language: English
  • ISSN: 1992-1950
  • DOI: 10.5897/IJPS
  • Start Year: 2006
  • Published Articles: 2569

Full Length Research Paper

Application of data mining in telecommunication industry

U. F. Eze*
  • U. F. Eze*
  • Department of Information Management Technology, Federal University of Technology, Owerri, Nigeria.
  • Google Scholar
C. J. Onwuegbuchulam
  • C. J. Onwuegbuchulam
  • Department of Consumer and Sales, Etisalat Communication Company, Nigeria.
  • Google Scholar
C. H. Ugwuishiwu
  • C. H. Ugwuishiwu
  • Department of Computer Science, University of Nigeria, Nsukka, Nigeria.
  • Google Scholar
S. Diala
  • S. Diala
  • Department of Computer Science, Federal University of Technology, Owerri, Nigeria.
  • Google Scholar

  •  Received: 06 December 2016
  •  Accepted: 08 March 2017
  •  Published: 30 March 2017


This paper applied a data mining model in sales and marketing department of Telecommunication Industry (TI) in Nigeria.  The motivation behind the paper is as a result of competitive challenges facing most TI sales and marketing departments globally such as inability in gaining precise view of targeted data, inability to translate and formulate business question correctly and Problem of addressing data quality. The aim of this research work is to develop and implement a model that would be used to retain existing customers, attract new ones, effectively manage and allocate resources, goods and services in TI. The data mining techniques used were classification, association, sequence discovery, visualization and prediction. The tools used to implement the model were PHP, JavaScript, CSS and HTML. Telecommunication Service Providers (TSP) considered were Mobile Telephone Networks (MTN), GlobaCom (GLO), Airtel and emerging telecommunication markets (EMTs) also known as Etisalat. Three products on sales and marketing department of TI such as Airtime, Electronic Recharge (e-top up) and SIM card sales were considered. The training data used for model exploratory analysis range from 2008 to 2015 (eight years) and was collected from historical sales records of EMTs. The data were cleaned and transformed. The enhanced system was achieved through the implementation of the model which proves to be more efficient than the existing system. The model implemented was able to extract relevance information from database of TI and makes sales forecast for subsequent year. Therefore the system is recommended to be used by the TI to enhance their productivity.

Key words: Telecommunication service provider, data mining, data mining technique, model, implementation.