# Robust portfolio optimization model for electronic coupon allocation

arXiv: https://arxiv.org/abs/2405.12865 · HTML: https://mlsanity.com/paper/2405.12865/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 May 2024.

## Built on by (most cited first, 4 of 4)

- [Robust portfolio optimization for recommender systems considering uncertainty of estimated statistics](https://mlsanity.com/paper/2406.10250/) (2024)
- [Balancing Immediate Revenue and Future Off-Policy Evaluation in Coupon Allocation](https://mlsanity.com/paper/2407.11039/) (2024)
- [Subset Selection for Stratified Sampling in Online Controlled Experiments](https://mlsanity.com/paper/2509.15576/) (2025)
- [Robust personalized pricing under uncertainty of purchase probabilities](https://mlsanity.com/paper/2407.15332/) (2024)

## Abstract (arXiv)

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.