How Do Digital Advertising Auctions Impact Product Prices?

共同价值拍卖 投标 杠杆(统计) 产品(数学) 业务 匹配(统计) 广告 计算机科学 微观经济学 经济 营销 数学 统计 几何学 机器学习
作者
Dirk Bergemann,Alessandro Bonatti,Nicholas C. Wu
出处
期刊:Cornell University - arXiv
标识
DOI:10.48550/arxiv.2304.08432
摘要

We ask how the advertising mechanisms of digital platforms impact product prices. We present a model that integrates three fundamental features of digital advertising markets: (i) advertisers can reach customers on and off-platform, (ii) additional data enhances the value of matching advertisers and consumers, and (iii) bidding follows auction-like mechanisms. We compare data-augmented auctions, which leverage the platform's data advantage to improve match quality, with managed campaign mechanisms, where advertisers' budgets are transformed into personalized matches and prices through auto-bidding algorithms. In data-augmented second-price auctions, advertisers increase off-platform product prices to boost their competitiveness on-platform. This leads to socially efficient allocations on-platform, but inefficient allocations off-platform due to high product prices. The platform-optimal mechanism is a sophisticated managed campaign that conditions on-platform prices for sponsored products on off-platform prices set by all advertisers. Relative to auctions, the optimal managed campaign raises off-platform product prices and further reduces consumer surplus.
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