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Segmentation of telecom customers based on customer value by decision tree model

机译:通过决策树模型基于客户价值对电信客户进行细分

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摘要

The more the telecom services marketing paradigm evolves, the more important it becomes to retain high value customers. Traditional customer segmentation methods based on experience or ARPU (Average Revenue per User) consider neither customers' future revenue nor the cost of servicing customers of different types. Therefore, it is very difficult to effectively identify high-value customers. In this paper, we propose a novel customer segmentation method based on customer lifecycle, which includes five decision models, i.e. current value, historic value, prediction of long-term value, credit and loyalty. Due to the difficulty of quantitative computation of long-term value, credit and loyalty, a decision tree method is used to extract important parameters related to long-term value, credit and loyalty. Then a judgments matrix formulated on the basis of characteristics of data and the experience of business experts is presented. Finally a simple and practical customer value evaluation system is built. This model is applied to telecom operators in a province in China and good accuracy is achieved.
机译:电信服务营销范式发展的越多,保留高价值客户就变得越重要。传统的基于经验或ARPU(每用户平均收入)的客户细分方法既不考虑客户的未来收入,也不考虑服务于不同类型客户的成本。因此,很难有效地识别高价值客户。本文提出了一种基于客户生命周期的新型客户细分方法,该方法包括当前价值,历史价值,长期价值预测,信誉和忠诚度五个决策模型。由于难以量化长期价值,信用和忠诚度,因此采用决策树方法提取与长期价值,信用和忠诚度有关的重要参数。然后提出了基于数据特征和业务专家经验制定的判断矩阵。最后,构建了一个简单实用的客户价值评估系统。该模型适用于中国某省的电信运营商,并且具有良好的准确性。

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