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CDR Analysis Based Telco Churn Prediction and Customer Behavior Insights: A Case Study

机译:基于CDR分析的Telco Churn预测和客户行为见解:一个案例研究

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Telecom churn has emerged as the single largest cause of revenue erosion for telecom operators. Predicting churners from the demographic and behavioral information of customers has been a topic of active research interest and industrial practice. In this case study paper, we present our experience of participating in a competitive evaluation for churn prediction and customer insights for a leading Asian telecom operator. We build a data mining model to predict churners using key performance indicators (KPI) based on customer Call Detail Records (CDR) and additional customer data available with the operator. Further, we analyze the social network formed between the (prepaid and postpaid) churners as well as the entire subscriber base. Our churn prediction method provided a lift of 8.4 over a nominal churn rate of 4.17% on 10% of the prepaid talking subscriber base on test data, and a lift of 7.62 on a nominal churn rate of 7.3% as reported in the customer evaluation on unseen data. This outperformed next best competitor in the study by more than twice. We also correlate social behavior patterns for churners and overall subscriber base. Our study indicates strong socially influenced churn among postpaid subscribers, in contrast with the prepaid subscribers. Our work provides guidelines and a template for conducting similar real-world studies for large telecom operators.
机译:电信流失已成为电信运营商收入侵蚀的最大原因。从客户的人口统计和行为信息预测搅拌一直是积极研究兴趣和工业实践的主题。在本案的研究文件中,我们展示了我们参与竞争评估的流失评估,并为领先的亚洲电信运营商进行竞争评估。我们构建数据挖掘模型,以根据客户呼叫详细记录(CDR)和运营商可用的其他客户数据来预测使用关键性能指标(KPI)的搅拌器。此外,我们分析了(预付和后付费)嵌入式以及整个用户群之间形成的社交网络。我们的潮流预测方法提供了8.4的电梯,标称流失率为4.17%的预付费谈话用户底座,在测试数据上的预付费谈话用户底座,并在客户评估中报告的标称流失率为7.62的电梯看不见的数据。这在研究中表现出了两次的下一个最佳竞争对手。我们还将搅拌器和整体用户群相关联。我们的研究表明,与预付用户相比,后付费用户在后付费用户之间的流失很强。我们的工作提供了指导方针和模板,用于对大型电信运营商进行类似的真实研究。

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