基于数据挖掘的电信行业客户流失预测

Lawchak Fadhil Khalid, Adnan Mohsin Abdulazeez, D. Zeebaree, F. Y. Ahmed, D. A. Zebari
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引用次数: 6

摘要

如今,许多企业和组织已经开始收集他们未来和现在的客户的数据,以评估流失率,防止潜在客户的流失,同时也保持现有的客户,让他们高兴。然而,具有挑战性的部分不是收集数据,而是在处理这些数据并根据收集到的信息对消费者进行细分时出现的问题。本文旨在研究数据挖掘在识别企业潜在流失人员方面的潜力,尤其关注电信行业。进行了许多实验,并测试了各种分类算法,以评估其预测潜在流失的影响和能力,因为这是企业保持客户满意并订阅其服务的关键信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Customer Churn Prediction in Telecommunications Industry Based on Data Mining
Nowadays, many businesses and organizations have begun to collect data on their future and current customers to evaluate churning rate and prevent the loss of potential customers while also keeping the current customers and making them happy. The challenging part, however, is not gathering the data, rather, it arises when these data are processed, and consumers are segmented based on the information collected. This paper aims to investigate the potentials of Data Mining in identifying potential churners from a business and more especially focusing on the Telecom industry. Many experiments are carried out, and various classification algorithms are tested to assess their impact and capability in predicting the potential churners, as this is a crucial information for businesses to keep their customers happy and subscribed to their services.
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