Impression Effect vs. Click-through Effect: Mechanism Design of Online Advertising

Search advertising and display advertising are two major online advertising formats. Search advertising emphasizes ads’ click-through effect. Advertisers only pay when users click the link of their ads. Traditional display advertising emphasizes ads’ impression effect. Most display ads are charged based on the number of views on the ads. Considering that most online ads increase brand awareness (impression effect) and directly promote sales (click-through effect), the not-emphasized effect in search advertising or display advertising actually has a significant impact on the market outcome. However, these impacts have been largely ignored. In this paper, we examine various mechanisms in search and display advertising by considering both ads’ impression effect and click-through effect. Interestingly, we show a seesaw relationship between ads’ two effects in search advertising. The advertiser whose advertisement has a strong click-through effect benefits relatively less from its impression effect. In display advertising, the real-time-bidding (RTB) mechanism considers both ads’ impression effect and click-through effect. It allows a publisher to gain more surplus than that through a static auction. However, we show that RTB is associated with a high risk of market failure

Three Essays on Managing Customer-Based Strategies: A Pricing and Revenue Management Approach

Many firms and organizations with already-optimized business functions are under market pressure to protect their narrow profit margins. Their need for supplemental and reliable revenues calls for performance optimization beyond the core business functions. Motivated by applications from online social media and the airline industry, in my dissertation, I focus on the revenue management and pricing decisions of customer-based plans and programs. More formally, the research question addressed in this study is: How can firms effectively use customer-based pricing strategies to boost revenues? My dissertation consists of three essays. In the first essay, I analyze the ongoing competition among online social media (OSMs) to attract users. Concentrating on the importance of community retention and expansion to OSMs in preserving financially sustainable business models, I investigate whether OSMs should develop revenue sharing programs and reward their contributing users from their limited revenue streams. I present a duopoly OSM game (with a less favourable and a more favourable OSM) in which heterogeneous users choose their levels of contribution with respect to each OSM based on their preferences. In this chapter, I explore how online users’ actions and perspectives impact the outcome of the competition among OSMs. Furthermore, I investigate how small social media firms can compete with a dominant firm in the market. In the second essay, I study the role of ancillary revenue and its significance for industries such as airlines. These firms can barely survive without ancillary fees, even when their capacities are almost fully utilized. I consider the case in which customers-changing rates between flights are stochastic but decreasing with reference to the change fees. In this essay, I examine how firms should design change fees to manage customers’ switching behaviour. Specifically, I incorporate change fee revenues as a portion of total revenue structure and investigate how firms should update their markdown pricing strategies when they face price-tracking customers. In the third essay, I focus on the dynamics between a firm and customers who are uncertain about their future travel plans. While the firm maximizes its revenue by imposing optimal change fees, customers consider their travel plan uncertainties and maximize their utilities by responding strategically to these fares. In this study, I seek to answer two important policy questions: Although imposing a change fee could increase total revenue, does it burden the firm with a lower customer demand? How should the optimal monopolistic price be set with the presence of a change fee? Without imposing any distributional assumptions, I analytically derive each market player’s best reaction to the other to prescribe the characteristics of the firm/customer interaction equilibrium

Revenue management in online advertising

Online advertising is a multibillion-dollar business with a promising revenue increase for the coming years. Web publishers that generate revenues from online advertising face several challenging decisions. They need to decide on how many advertising slots to have on their website, whether to hire a sales force to attract advertisers to post ads on their website or rely on advertising networks, how many impressions to promise to deliver, and how much to charge, etc. Revenue management, in particular pricing, is considered one of the most challenging tasks and currently ad-hoc approaches are frequently used. In this dissertation, we provide systematic approaches for managing revenues in online display advertising. In the first chapter, we consider a web publisher facing uncertain demand from advertisers requesting space on its website, and an uncertain supply of impressions from viewers visiting the website. Formulating the problem as a novel queuing system we show, for example, that the optimal cost-per-impression (CPM) can increase in the number of ads rotated in a slot, which goes against the intuition of supply and demand. In the second chapter, we consider a different pricing scheme, the so-called cost-per-click scheme. Formulating the problem as another novel queuing system, we show that the general heuristic applied by practitioners to convert between the CPC and CPM pricing schemes using the so-called click-through rate (CTR), can be misleading. In the third chapter, we explore the interactions of two web publishers in a competitive setting and provide various interesting insights about their strategic pricing behavior at equilibrium. Lastly, In the fourth chapter, we obtain the optimality conditions for the advertisers' demand process when the demand distribution, instead of being Poisson, follows an arbitrary continuous distribution

Cost-per-click pricing for display advertising

Display advertising is a $25 billion business with a promising upward revenue trend. In this paper, we consider an online display advertising setting in which a web publisher posts display ads on its website and charges based on the cost-per-click (CPC) pricing scheme while promising to deliver a certain number of clicks to the ads posted. The publisher is faced with uncertain demand for advertising slots and uncertain traffic to its website as well as uncertain click behavior of visitors. We formulate the problem as a novel queueing system, where the slots correspond to service channels with the service rate of each server inversely related to the number of active servers. We obtain the closed-form solution for the steady-state probabilities of the number of ads in the publisher's system. We determine the publisher's optimal price to charge per click and show that it can increase in the number of advertising slots and the number of promised clicks. We show that the common heuristic used by many web publishers to convert between the cost-per-click and cost-per-impression pricing schemes using the so-called click-through-rate can be misleading as it may incur web publishers substantial revenue loss. We provide an alternative explanation for the phenomenon observed by several publishers that the click-through-rate tends to drop when they switch from the cost-per-click to cost-per-impression pricing scheme

Competition and Yield Optimization in Ad Exchanges

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