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arXiv · 2401.01656

Deep Automated Mechanism Design for Integrating Ad Auction and Allocation in Feed

Xuejian Li·Ze Wang·Bingqi Zhu·Fei He·Yongkang Wang·Xingxing Wang
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Abstract

E-commerce platforms usually present an ordered list, mixed with several organic items and an advertisement, in response to each user's page view request. This list, the outcome of ad auction and allocation processes, directly impacts the platform's ad revenue and gross merchandise volume (GMV). Specifically, the ad auction determines which ad is displayed and the corresponding payment, while the ad allocation decides the display positions of the advertisement and organic items. The prevalent methods of segregating the ad auction and allocation into two distinct stages face two problems: 1) Ad auction does not consider externalities, such as the influence of actual display position and context on ad Click-Through Rate (CTR); 2) The ad allocation, which utilizes the auction-winning ad's payment to determine the display position dynamically, fails to maintain incentive compatibility (IC) for the advertisement. For instance, in the auction stage employing the traditional Generalized Second Price (GSP) , even if the winning ad increases its bid, its payment remains unchanged. This implies that the advertisement cannot secure a better position and thus loses the opportunity to achieve higher utility in the subsequent ad allocation stage. Previous research often focused on one of the two stages, neglecting the two-stage problem, which may result in suboptimal outcomes...

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Xuejian Li, Ze Wang, Bingqi Zhu, Fei He, Yongkang Wang, Xingxing Wang. 2024-04-11. Deep Automated Mechanism Design for Integrating Ad Auction and Allocation in Feed. https://arxiv.org/abs/2401.01656

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