Promotional displays, such as end‐of‐aisle displays, provide a stimulus for discretionary and incremental sales at grocery stores, offering a powerful yet affordable tool to boost profit. In this study, we examine a store manager's choice of which stock‐keeping units (SKUs) from a given category to assign to a promotional display space. While the academic literature and retail software solution providers offer a variety of optimization solutions for the assortment optimization problem, there is very little guidance for retailers on how to optimally determine when and what products to place on their promotional display space. Consequently, retailers often default to simple heuristics, which are typically suboptimal from a profit maximization standpoint, when making this decision. Thus, there is a need for a decision support tool to facilitate the product selection for promotional display space. Using a grocery store sales transaction data set, we demonstrate how to measure the incremental lift in sales of placing a particular SKU on promotional display space. Our optimization model includes the incremental lifts (from the estimation method) combined with the estimated base‐sales rates and profit margins of each SKU so that the profit‐maximizing SKU can be chosen for a promotional display space for each week of the year. Placing a SKU on promotional display can result in a significant lift in sales. For example, the estimated average display effect (i.e., sales lift) for the beer category across all SKUs and all weeks is 27%, which makes promotional display a very effective tool for stimulating incremental product sales. Overall, our methodology results in at least 1.6 times improvement in incremental profit when compared to a common industry benchmark. We also test our methodology on two additional product categories and demonstrate that it performs equally well across product categories. Our work provides an easy‐to‐implement, promotional display SKU‐selection methodology that includes both an estimation and an optimization model. Our estimation model can handle an extensive and complex product assortment and accounts for important aspects of promotional activities such as the cannibalization of the inner aisle sales and halo effects. Our optimization model is flexible enough to consider practical aspects such as common business rules that restrict the selection of the same SKU over a consecutive set of weeks, display‐related changeover costs, and slotting fees offered by the manufacturers. Overall, our study underscores the importance of making effective promotional display decisions.

中文翻译：

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优化杂货店零售商促销展示空间的库存单位选择

促销显示屏，例如过道显示屏，可以刺激杂货店的随意销售和增量销售，提供功能强大但价格合理的工具来增加利润。在这项研究中，我们研究了商店经理从给定类别中选择要分配给促销展示空间的哪些库存单位（SKU）的选择。尽管学术文献和零售软件解决方案提供商为分类优化问题提供了多种优化解决方案，但对于零售商如何最佳确定何时以及在其促销展示空间上放置什么产品的指导却很少。因此，零售商在做出此决定时通常会默认简单的试探法，从利润最大化的角度来看，这些试探法通常不是最优的。从而，需要一种决策支持工具来促进促销展示空间的产品选择。使用杂货店销售交易数据集，我们演示了如何测量在促销展示空间上放置特定SKU的销售增量。我们的优化模型包括增量提升（通过估算方法得出）与每个SKU的估计基本销售率和利润率相结合，以便可以在一年的每个星期为促销展示空间选择利润最大化的SKU。将SKU放置在促销显示器上可以大大提高销售量。例如，在所有SKU和整个星期内，啤酒类别的估计平均展示效果（即销售提升）为27％，这使促销展示成为刺激增量产品销售的非常有效的工具。总体，与常见的行业基准相比，我们的方法至少可将增量利润提高1.6倍。我们还对另外两个产品类别测试了我们的方法，并证明了其在所有产品类别中的效果均相同。我们的工作提供了一种易于实施的促销显示SKU选择方法，其中包括估算模型和优化模型。我们的估算模型可以处理广泛而复杂的产品分类，并可以解释促销活动的重要方面，例如内部通道销售的蚕食和光环效应。我们的优化模型具有足够的灵活性，可以考虑实际方面，例如限制连续几周选择同一SKU的通用业务规则，与显示相关的转换成本，和制造商提供的进场费。总体而言，我们的研究强调了做出有效的促销展示决策的重要性。