Maximizing customers' lifetime value using limited marketing resources

IF 3.6 3区 管理学 Q2 BUSINESS
Mage Marmol, Anita Goyal, P. Copado-Mendez, Javier Panadero, A. Juan
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引用次数: 3

Abstract

PurposeFor any given customer, his/her profitability for a business enterprise can be estimated by the so-called customer lifetime value (CLV). One specific goal for many enterprises consists in maximizing the aggregated CLV associated with its set of customers. To achieve this goal, a company uses marketing resources (e.g. marketing campaigns), which are usually expensive.Design/methodology/approachThis paper proposes a formal model of the Customer Life Value problem inspired by the uncapacitated facility location problem.FindingsThe computational experiments conducted by the authors illustrate the potential of the approach when compared with a standard (non-algorithm-supported) one.Originality/valueThe approach leads up to the economic trade-off between the volume of the employed resources and the aggregated CLV, i.e. the higher the number of resources utilized, but also the higher the cost of achieving this level of lifetime value. Hence, the number of resources to be “activated” has to be decided, and the effect of each of these resources on each CLV will depend upon how “close” the resource is from the corresponding customer (i.e. how large will the impact of the active resource on the customer).
利用有限的营销资源最大化客户终身价值
对于任何给定的客户,他/她对企业的盈利能力可以通过所谓的客户生命周期价值(CLV)来估计。许多企业的一个特定目标是最大化与其客户集相关联的聚合CLV。为了实现这一目标,公司使用营销资源(如营销活动),这通常是昂贵的。设计/方法/途径受无容量设施选址问题的启发,本文提出了客户生命价值问题的形式化模型。作者进行的计算实验说明了与标准(非算法支持)方法相比,该方法的潜力。原创性/价值这种方法导致了在使用资源的数量和聚合CLV之间的经济权衡,即使用的资源数量越多,但实现这种终身价值水平的成本也就越高。因此,必须决定要“激活”的资源数量,并且这些资源对每个CLV的影响将取决于资源与相应客户的“接近”程度(即,活动资源对客户的影响有多大)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.00
自引率
9.10%
发文量
64
期刊介绍: Marketing Intelligence & Planning (MIP) facilitates communication between researchers and practitioners, providing the users of research with a wealth of robust and relevant information. At a time when some journals are losing their relevance to industry and practical requirements, MIP successfully offers a bridge between academic and practitioner thinking, while retaining a high level of scientific rigour.
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