Robust portfolio optimization model for electronic coupon allocation

TL;DR

This paper introduces a robust portfolio optimization model for electronic coupon allocation that handles multiple coupon types and outperforms traditional models in increasing sales uplift, validated with real data.

Contribution

It develops a robust optimization approach for coupon allocation across six coupon types, improving sales uplift over existing models.

Findings

Robust model achieves higher sales uplift than traditional models.

Handling six coupon types increases allocation accuracy.

Numerical experiments validate the model's effectiveness.

Abstract

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.