Due to low switching costs and stiff competition, customer relationship management has become a central component in the marketing strategy of telecommunication service providers. Since the costs of acquiring a new customer are five times higher than the costs of maintaining an existing customer, telecommunication service providers are eager to reduce the churn rate. A solid understanding of customer churn behavior can help to address this problem. Reducing the churn rate can translate into significant revenue gains and might provide the edge to outperform the competitor. In this paper, we predict the propensity to churn for customers of a Dutch telecommunication service provider by employing a duration model. While predicting churn, we simultaneously predict the reason for which the customer churns, using a competing risks model. Since the telecommunication service provider has valuable textual data based on transcripts of calls between customers and the customer service center, we incorporate topics extracted from this textual data as variables in our models, by employing Latent Dirichlet Allocation (LDA). We compare four models and find that the models that have incorporated topic variables usually yield the best churn forecasts. Also, the investigated models beat the considered benchmark model, which is the model currently deployed at the telecommunication service provider.

由于较低的交换成本和激烈的竞争，客户关系管理已成为电信服务提供商营销策略的核心组成部分。由于获得新客户的成本是维持现有客户成本的五倍，因此电信服务提供商急切地希望降低客户流失率。对客户流失行为的深入了解可以帮助解决此问题。降低客户流失率可以转化为可观的收入增长，并可能提供超越竞争对手的优势。在本文中，我们通过采用持续时间模型来预测荷兰电信服务提供商的客户流失的倾向。在预测客户流失的同时，我们使用竞争风险模型同时预测客户流失的原因。由于电信服务提供商拥有基于客户和客户服务中心之间通话记录的有价值的文本数据，因此，我们通过使用潜在狄利克雷分配（LDA），将从该文本数据中提取的主题作为变量纳入我们的模型中。我们比较了四个模型，发现合并了主题变量的模型通常会产生最佳的客户流失预测。而且，所研究的模型优于考虑的基准模型，该模型是当前在电信服务提供商处部署的模型。我们比较了四个模型，发现合并了主题变量的模型通常会产生最佳的客户流失预测。而且，所研究的模型优于考虑的基准模型，该模型是当前在电信服务提供商处部署的模型。我们比较了四个模型，发现合并了主题变量的模型通常会产生最佳的客户流失预测。而且，所研究的模型优于考虑的基准模型，该模型是当前在电信服务提供商处部署的模型。