This paper explores the application of Shapley Value Regression in dissecting marketing performance at channel-partner level, complementing channel-level Marketing Mix Modeling (MMM). Utilizing real-world data from the financial services industry, we demonstrate the practicality of Shapley Value Regression in evaluating individual partner contributions. Although structured in-field testing along with cooperative game theory is most accurate, it can often be highly complex and expensive to conduct. Shapley Value Regression is thus a more feasible approach to disentangle the influence of each marketing partner within a marketing channel. We also propose a simple method to derive adjusted coefficients of Shapley Value Regression and compares it with alternative approaches.

本文探讨了Shapley Value Regression在分解渠道合作伙伴层面的营销绩效中的应用，作为渠道级别的营销组合建模（MMM）的补充。利用金融服务行业的真实数据，我们展示了Shapley Value Regression在评估个体合作伙伴贡献方面的实用性。尽管结构化的现场测试和合作博弈理论是最准确的，但往往会非常复杂和昂贵。因此，Shapley Value Regression是一种更可行的方法，用于解开营销渠道中每个营销合作伙伴的影响。我们还提出了一种简单的方法来推导Shapley Value Regression的调整系数，并将其与替代方法进行比较。

利用市场组合模型(MMM)和Shapley值回归量化渠道合作伙伴层面的市场营销绩效