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Aplicação de Mineração de Dados para Detecção de Potenciais Churns em Empresa do Segmento SAAS
Author(s) -
Leonardo Lucas de Melo,
Rafael Ballottin Martins
Publication year - 2020
Publication title -
anais do xi computer on the beach - cotb '20
Language(s) - English
Resource type - Conference proceedings
DOI - 10.14210/cotb.v11n1.p034-036
Subject(s) - software as a service , trace (psycholinguistics) , payment , computer science , process (computing) , business , world wide web , software , operating system , linguistics , philosophy , software development
This paper tackles the problem of companies that offer subscription services, plans or any other recurring method of payment. In this commercialization model, it is important to keep the churn rate low, but to define strategies for reduce churn rate it is needed to identify what are the main reasons for losing customers. The application of data mining techniques may assist to find out patterns that can trace the most likely customers to become churns. Through this research, using the data mining process, it was possible to identify that, among other factors, the non-utilization of the main system modules and the high default rates corroborates for customers to become churn.

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