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.

翻译：本文探讨了Shapley值回归在剖析渠道合作伙伴层面营销表现中的应用，这是对渠道层面营销组合模型（MMM）的补充。利用金融服务业真实数据，我们验证了Shapley值回归在评估单个合作伙伴贡献方面的实用性。尽管结合合作博弈理论的结构化现场测试最为精确，但其操作复杂度高且成本昂贵。因此，Shapley值回归成为分解营销渠道中各合作伙伴影响力的更可行方法。我们还提出了一种简单方法推导Shapley值回归的调整系数，并与替代方法进行了对比。