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 compare it with alternative approaches.

翻译：本文探讨了沙普利值回归在剖析渠道合作伙伴层面营销绩效中的应用，作为对渠道级营销组合模型（MMM）的补充。利用金融服务业真实数据，我们验证了沙普利值回归在评估个体合作伙伴贡献方面的实用性。尽管结合合作博弈理论的实地结构化测试最为精确，但实施过程往往高度复杂且成本高昂。因此，沙普利值回归是厘清营销渠道内各合作方影响力的更可行方案。我们还提出了一种简单方法以推导沙普利值回归的调整系数，并将其与替代方法进行了比较。