Currently, many e-commerce websites issue online/electronic coupons as an effective tool for promoting sales of various products and services. We focus on the problem of optimally allocating coupons to customers subject to a budget constraint on an e-commerce website. We apply a robust portfolio optimization model based on customer segmentation to the coupon allocation problem. We also validate the efficacy of our method through numerical experiments using actual data from randomly distributed coupons. Main contributions of our research are twofold. First, we handle six types of coupons, thereby making it extremely difficult to accurately estimate the difference in the effects of various coupons. Second, we demonstrate from detailed numerical results that the robust optimization model achieved larger uplifts of sales than did the commonly-used multiple-choice knapsack model and the conventional mean-variance optimization model. Our results open up great potential for robust portfolio optimization as an effective tool for practical coupon allocation.

翻译：当前，众多电子商务网站通过发放电子优惠券作为促进各类商品与服务销售的有效手段。本文聚焦于在预算约束下，为电商网站客户实现优惠券最优分配的问题。我们将基于客户细分的稳健投资组合优化模型应用于优惠券分配场景，并通过基于实际随机发放优惠券数据的数值实验验证了该方法的效果。本研究的主要贡献体现在两个方面：首先，我们处理了六种不同类型的优惠券，这极大增加了准确估计各类优惠券效果差异的难度；其次，详细的数值结果表明，稳健优化模型相较于常用的多选背包模型和传统均值-方差优化模型实现了更高的销售额增长。研究结果揭示了稳健投资组合优化作为实际优惠券分配有效工具的广阔潜力。