Should Ad Exchanges Subsidize Advertisers to Acquire Targeting Data?
研究了广告交易平台通过三种补贴框架（全部补贴、赢家补贴、输家补贴）激励广告商购买数据以提升平台净收入的效果，发现赢家补贴的优劣取决于数据获取成本、对广告选择的影响及印象价值分布。
Large volumes of online impressions are sold daily via real-time auctions to deliver targeted advertisements to consumers. Advertisers use data to learn about user preferences and select the most appropriate ad for each user, which also help them optimize their bids in an ad auction. Although ad exchanges may provide some user data to advertisers, they are usually limited, and advertisers often acquire data from various sources to improve targeting performance. The acquisition of such data can significantly influence the revenue of the ad exchange, which motivates ad exchanges to take actions that reduce advertisers’ data acquisition costs and encourage them to buy data. In this study, we propose three subsidy frameworks to increase ad exchange revenue by inducing more advertisers to acquire data: all subsidized, winner subsidized, and loser subsidized. Using a stylized model, we analyze the impact of subsidy provisions on the platform’s net revenue. Our results show that winner subsidized can be better or worse than all subsidized depending on the cost of data acquisition, its beneficial impact on ad selection, and the distribution of impression values.