Title: Competition and Yield Optimization in Ad Exchanges
Description: Ad Exchanges are emerging Internet markets where advertisers may purchase display ad placements, in real-time and based on specific viewer information, directly from publishers via a simple auction mechanism. The presence of such channels presents a host of new strategic and tactical questions for publishers. How should the supply of impressions be divided between bilateral contracts and exchanges? How should auctions be designed to maximize profits? What is the role of user information and to what extent should it be disclosed? In this thesis, we develop a novel framework to address some of these questions. We first study how publishers should allocate their inventory in the presence of these new markets when traditional reservation-based ad contracts are available. We then study the competitive landscape that arises in Ad Exchanges and the implications for publishers' decisions. Traditionally, an advertiser would buy display ad placements by negotiating deals directly with a publisher, and signing an agreement, called a guaranteed contract.

These deals usually take the form of a specific number of ad impressions reserved over a particular time horizon. In light of the growing market of Ad Exchanges, publishers face new challenges in choosing between the allocation of contract-based reservation ads and spot market ads. In this setting, the publisher should take into account the tradeoff between short-term revenue from an Ad Exchange and the long-term impact of assigning high quality impressions to the reservations (typically measured by the click-through rate). In the first part of this thesis, we formalize this combined optimization problem as a stochastic control problem and derive an efficient policy for online ad allocation in settings with general joint distribution over placement quality and exchange bids, where the exchange bids are assumed to be exogenous and independent of the decisions of the publishers. We prove asymptotic optimality of this policy in terms of any arbitrary trade-off between quality of delivered reservation ads and revenue from the exchange, and provide a bound for its convergence rate to the optimal policy.

We also give experimental results on data derived from real publisher inventory, showing that our policy can achieve any Pareto-optimal point on the quality vs. revenue curve. In the second part of this thesis, we relax the assumption of exogenous bids in the Ad Exchange and study in more detail the competitive landscape that arises in Ad Exchanges and the implications for publishers' decisions. Typically, advertisers join these markets with a pre-specified budget and participate in multiple second-price auctions over the length of a campaign. We introduce the novel notion of a Fluid Mean Field Equilibrium (FMFE) to study the dynamic bidding strategies of budget-constrained advertisers in these repeated auctions. This concept is based on a mean field approximation to relax the advertisers' informational requirements, together with a fluid approximation to handle the complex dynamics of the advertisers' control problems. Notably, we are able to derive a closed-form characterization of FMFE, which we use to study the auction design problem from the publisher's perspective focusing on three design decisions: (1) the reserve price; (2) the supply of impressions to the Exchange versus an alternative channel such as bilateral contracts; and (3) the disclosure of viewers' information.

Our results provide novel insights with regard to key auction design decisions that publishers face in these markets. In the third part of this thesis, we justify the use of the FMFE as an equilibrium concept in this setting by proving that the FMFE provides a good approximation to the rational behavior of agents in large markets. To do so, we consider a sequence of scaled systems with increasing market size;. In this regime we show that, when all advertisers implement the FMFE strategy, the relative profit obtained from any unilateral deviation that keeps track of all available information in the market becomes negligible as the scale of the market increases. Hence, a FMFE strategy indeed becomes a best response in large markets.