Improvement of a telecommunications company tariff policy taking into account subscribers’ preferences

Business Informatics. 2016. Vol. 36. No. 2. P. 7–15.

Tatiana K. Bogdanova, Dmitry Yu. Neklyudov

According to most analysts, the era of extensive growth in the telecommunications market has almost fi nished. The ongoing competition between leading telecommunications companies is bringing the problem of developing a rational telecommunications policy to the forefront. The ever-changing telecommunications market, subscribers’ preferences, the expanding variety of services, the need for updating user data, the inadequate effi ciency of the existing systems to form exact subscriber defi nitions demonstrate the need for more fl exible tariff methods and policy. In spite of Russian and foreign scientists taking into consideration the pricing problems in forming tariff plans, the main accent is placed on price formation according to the profi ts either of the whole telecommunications fi eld or company expenses in most attempts. The problem of diff erentiation of tariff plan characteristics with the purpose of subscribers’ preference calculations has not been suffi ciently explored. Moreover, the structural problems of tariff plans, where phone subscribers’ preferences should be taken into consideration, and the whole tariff policy, in which formation of the entire complex of existent and prospective tariff plans should be taken into consideration, have not been properly researched. For solving these problems, we have off ered a model of forming telecommunications company tariff policy using methods of intellectual data analysis and taking into consideration discovered preferences of subscribers and investors.

Keywords: моделирование, кластеризация, тарифный план, рынок телекоммуникационных услуг, тарифная политика, clustering, intelligent data analysis, economic-mathematical modeling, tariff policy, telecommunications, телекоммуникационная компания, consumers preferences, the segment profile, client life-time value, предпочтения абонентов, профиль абонентского потребления, долгосрочная ценность клиента, интеллектуальные методы анализа данных