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Churn management optimization with controllable marketing variables and associated management costs

机译：具有可控的营销变量和相关管理成本的客户流失管理优化

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摘要

In this paper, we propose a churn management model based on a partial least square (PLS) optimization method that explicitly considers the management costs of controllable marketing variables for a successful churn management program. A PLS prediction model is first calibrated to estimate the churn probabilities of customers. Then this PLS prediction model is transformed into a control model after relative management costs of controllable marketing variables are estimated through a triangulation method. Finally, a PLS optimization model with marketing objectives and constraints are specified and solved via a sequential quadratic programming method. In our experiments, we observe that while the training and test data sets are dramatically different in terms of churner distributions (50% vs. 1.8%), four controllable variables in three marketing strategies significantly changed through optimization process while other variables only marginally changed. We also observe that the most significant variable in a PLS prediction model does not necessarily change most significantly in our PLS optimization model due to the highest management cost associated, implying differences between a prediction and an optimization model. Finally, two marketing models designed for targeting the subsets of customers based on churn probability or management costs are presented and discussed.
机译：在本文中，我们提出了一种基于偏最小二乘（PLS）优化方法的客户流失管理模型，该模型明确考虑了成功的客户流失管理程序中可控营销变量的管理成本。首先对PLS预测模型进行校准，以估计客户的流失概率。然后，通过三角测量法估计了可控营销变量的相对管理成本后，将该PLS预测模型转换为控制模型。最后，通过顺序二次规划方法指定并求解了具有营销目标和约束条件的PLS优化模型。在我们的实验中，我们观察到，尽管训练和测试数据集的Churner分布存在显着差异（50％比1.8％），但三种营销策略中的四个可控变量在优化过程中发生了显着变化，而其他变量仅发生了少量变化。我们还观察到，由于相关的最高管理成本，PLS预测模型中最重要的变量不一定会在我们的PLS优化模型中发生最显着的变化，这意味着预测和优化模型之间存在差异。最后，介绍并讨论了两种基于流失概率或管理成本设计的，针对客户子集的营销模型。

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