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In a competitive market, adopting suitable business strategies is essential to satisfice and make clients loyal. This research aimed to identify profiles of clients that kept loyal to a telecom company and users that cancelled the service. We have considered reports from occurrences of the phone attendance service, registered to a private database, granted for this research. We have applied text mining for classification of occurrences, to avoid cancellation, and extraction of association rules, to understand the reasons that lead users to cancel the service. In the experienced conditions, the algorithms could predict cancellations with 97,02% accuracy. Besides, the most representative attributes for each class were extracted, providing a framework for strategic decision-making.

Mineração de Textos para Gestão de Clientes em Empresas de Telecomunicações