Information disclosure in real-time bidding advertising markets

Abstract

Real-time bidding (RTB) advertising is a fast-growing business model in online display advertising markets. Unlike the guaranteed display advertising, it utilizes programmatic instantaneous auction to price and sell ad inventory on a per-impression basis. RTB enbales advertisers to target audiences at demographic, psychographic or behavioral levels across a wide range of websites. In RTB markets, information about target audiences is usually disclosed to advertisers, while information about publishers (e.g. website ranking, advertising page) are typically not avaliable for advertisers, especially in real-time setting. This leads to a serious information asymmetry problem in RTB markets, which has significant influence on both advertisers' bidding strategies and publishers' revenues. In this paper, we study the information disclosure strategies of publishers in case when the disclosure may incur an extra cost. We address this information asymmetry problem by first formulating the RTB auction as an second-price sealed-bid game, then discussing equilibrium information disclosure strategies for publishers and also investigating advertisers' bidding strategies in the three information disclosure cases: all disclosed, non-disclosed, and partially disclosed. We find that non-disclosed and partially disclosed strategies may lead to an adverse selection effect, and high-quality publishers will be forced to quit the RTB markets.