Enabling customer relationship management in ISP services through mining usage patterns

Abstract

The monopoly of state ownership of telecommunication industry in Taiwan was lifted in 1997. In choosing an ISP, pricing was and still is a main differentiating factor in the mind of customers; however, service quality has emerged as a major concern among users lately. Management of ISP has discovered that service quality is important not only for attracting new customers, but, more importantly, for retaining existing customers who may otherwise be lured away by lower fees. Hence, it is essential to develop a CRM system, which could help keeping existing customers and exploring further business opportunities at the same time. In this study, we, based on the IP traffic data, developed a CRM systematic approach for a major ISP company in Taiwan to enhance customers' longer-term loyalty. This approach employs CRISP-DM methodology, and applies Attribute-Oriented Induction as the mining technique to discover network usage behaviors of customers, which help management identify usage pattern and also pinpoint the time when usage is excessively heavy. The former allows management to make effective personal calls for services or maintenance, and the latter presents opportunities for management to offer personalized cares and advanced products. Pixel-oriented visualization is applied to improve the understanding of mining results.