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Profit Maximization Analysis Based on Data Mining and the Exponential Retention Model Assumption with Respect to Customer Churn Problems

机译:基于数据挖掘和针对客户流失问题的指数保留模型假设的利润最大化分析

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Confronted with fierce competition, an increasing number of telecommunication companies in China realize that they can increase proflts by reducing the rate of customer churn rather than attracting the same number of new customers. Recently, the availability of big data has increased, which has stimulated the development of data mining techniques. Identifying methods by which to maximize proflts is vital for operators based on big data. Novelly, this paper studies three key factors of the customer churn problem, namely, churn rate, prediction performance, and retention capability. We propose a proflt function that maximizes proflts under different conditions and obtain favorable results in applying it to sample data from China Mobile Communications Corporation. Theoretically, about 7.72 million Chinese Yuan per month can be obtained by applying proposed model to China Mobile Group Guangxi Company Limited, making our research of great economic value.
机译:面对激烈的竞争,越来越多的中国电信公司意识到,通过降低客户流失率而不是吸引相同数量的新客户,它们可以提高利润。最近,大数据的可用性增加了,这刺激了数据挖掘技术的发展。识别最大化利润的方法对于基于大数据的运营商至关重要。新颖的是,本文研究了客户流失问题的三个关键因素,即流失率,预测性能和保留能力。我们提出了一个proflt函数,该函数可以在不同条件下最大化proflt,并在将其应用于中国移动通信公司的样本数据时获得良好的结果。从理论上讲,将建议的模型应用到中国移动通信集团广西有限公司,每月可获得约772万元人民币,这对我们的研究具有重要的经济价值。

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