In Pursuit of Enhanced Customer Retention Management: Review, Key Issues, and Future Directions

Eva Ascarza, S. Neslin, O. Netzer, Zachery Anderson, P. Fader, Sunil Gupta, Bruce G. S. Hardie, A. Lemmens, B. Libai, David Neal, F. Provost, Rom Y. Schrift
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引用次数: 98

Abstract

In today’s turbulent business environment, customer retention presents a significant challenge for many service companies. Academics have generated a large body of research that addresses part of that challenge—with a particular focus on predicting customer churn. However, several other equally important aspects of managing retention have not received similar level of attention, leaving many managerial problems not completely solved, and a program of academic research not completely aligned with managerial needs. Therefore, our goal is to draw on previous research and current practice to provide insights on managing retention and identify areas for future research. This examination leads us to advocate a broad perspective on customer retention. We propose a definition that extends the concept beyond the traditional binary retain/not retain view of retention. We discuss a variety of metrics to measure and monitor retention. We present an integrated framework for managing retention that leverages emerging opportunities offered by new data sources and new methodologies such as machine learning. We highlight the importance of distinguishing between which customers are at risk and which should be targeted—as they are not necessarily the same customers. We identify trade-offs between reactive and proactive retention programs, between short- and long-term remedies, and between discrete campaigns and continuous processes for managing retention. We identify several areas of research where further investigation will significantly enhance retention management.
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追求增强客户保留管理:回顾、关键问题和未来方向
在当今动荡的商业环境中,客户保留对许多服务公司来说是一个重大挑战。学者们已经进行了大量的研究,以解决这一挑战的一部分,并特别关注预测客户流失。然而,管理留用的其他几个同样重要的方面没有得到类似的重视,留下许多管理问题没有完全解决,学术研究计划没有完全符合管理需要。因此,我们的目标是借鉴以前的研究和当前的实践,为管理员工保留提供见解,并确定未来研究的领域。这一研究使我们提倡对客户留存率持广泛的看法。我们提出了一个扩展概念的定义,超越了传统的保留/不保留的二元保留观点。我们将讨论各种衡量和监控留存率的指标。我们提出了一个管理保留的综合框架,利用新数据源和新方法(如机器学习)提供的新机会。我们强调区分哪些客户有风险,哪些客户应该成为目标客户的重要性,因为他们不一定是相同的客户。我们确定了被动和主动保留计划之间的权衡,短期和长期补救措施之间的权衡,以及管理保留的离散活动和连续过程之间的权衡。我们确定了几个研究领域,进一步的调查将显著提高留用管理。
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