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arXiv · 2407.11039

Balancing Immediate Revenue and Future Off-Policy Evaluation in Coupon Allocation

Naoki Nishimura·Ken Kobayashi·Kazuhide Nakata
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Abstract

Coupon allocation drives customer purchases and boosts revenue. However, it presents a fundamental trade-off between exploiting the current optimal policy to maximize immediate revenue and exploring alternative policies to collect data for future policy improvement via off-policy evaluation (OPE). To balance this trade-off, we propose a novel approach that combines a model-based revenue maximization policy and a randomized exploration policy for data collection. Our framework enables flexible adjustment of the mixture ratio between these two policies to optimize the balance between short-term revenue and future policy improvement. We formulate the problem of determining the optimal mixture ratio as multi-objective optimization, enabling quantitative evaluation of this trade-off. We empirically verified the effectiveness of the proposed mixed policy using synthetic data. Our main contributions are: (1) Demonstrating a mixed policy combining deterministic and probabilistic policies, flexibly adjusting the data collection vs. revenue trade-off. (2) Formulating the optimal mixture ratio problem as multi-objective optimization, enabling quantitative evaluation of this trade-off.

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Naoki Nishimura, Ken Kobayashi, Kazuhide Nakata. 2024-07-06. Balancing Immediate Revenue and Future Off-Policy Evaluation in Coupon Allocation. https://arxiv.org/abs/2407.11039

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