Impact of Data Mining on Telecommunication Company Revenues
I. A. Kamani C Samarasinghe1, S. R. Kodituwakku2, Y. P. R. D. Yapa3
1I A Kamani C Samarasinghe, M.Phil, Post Graduate Institute of Science (PGIS), University of Peradeniya, Sri Lanka..
2Saluka R. Kodituwakku, Professor, Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya, (Peradeniya). Sri Lanka.
3Roshan D. Yapa, Lecturer, Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya, (Peradeniya). Sri Lanka.
Manuscript received on May 12, 2016. | Revised Manuscript received on May 18, 2016. | Manuscript published on July 05, 2016. | PP: 37-41 | Volume-6 Issue-3, July 2016. | Retrieval Number: C2874076316
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Rapid advancement of the technology has made the telecommunication sector very competitive. In order to keep up with the competition, telecommunication operators have to identify the exact needs of the customers and offer services in-line with customer needs. The aim of this research is to investigate the applicability of data mining in identifying customer needs and how it can be adapted to increase the revenue of telecommunication companies. The objectives of this study include an investigation into the relationship between data mining practices and customer behavior patterns, relationship between customer needs and products or services, relationship between new product design initiatives and revenue increases of the companies, the impact of data mining on the revenue of telecommunications companies, and the development of a data mining framework to improve the overall Average Revenue Per User (ARPU) levels in the industry in addition to the designing of a Business Intelligence (BI) tool to enhance decision making processes for improving the overall ARPU levels of the industry. Firstly, the conceptual model is developed based on the feedback of a sample of employees who hold positions in the telecommunications sector. This model has four main variables; data mining, customer behavior, product and increased revenue. Secondly, a preliminary study was carried out to test the variables and to find out how data mining can be applied to identify customer needs and how companies can benefit from using data mining techniques in their businesses. Next, a Data Mining framework was developed to make sure that the expected results could be received from the data mining exercise in place. Finally, a Business Intelligence tool was developed to validate the data mining framework. The preliminary study revealed a clear relationship between the variables of the conceptual framework. Furthermore, it was evident that data mining could lead to better business decisions, apart from the other key benefits of using it, such as timely delivery of services and an increase in customer satisfaction which may affect the revenue of the company. The post survey validation from the target users (managers of telecom companies) indicated that the proposed BI tool is capable of retrieving much needed information for business decisions, which would lead to increased revenues of the companies. The long term results are likely to be positive in this context and it is also evident that the role of data mining can be expanded by the companies and that this practice could eventually lead to companies providing markets with the exact requirements.
Keywords: Business Intelligence, data mining, revenues, telecommunication