Ad exchanges aren't second-price auctions.
About a year ago my colleague Edward Montes wrote a column titled "The First Rule of Advertising Exchanges - There Are No Advertising Exchanges" on ClickZ.
In the column, Ed concludes that there is no such thing as an ad exchange because of the lack of price transparency to the buyer, especially when the seller can see buyer bids.
I conclude that the second rule of advertising exchanges is that ad exchanges are not second-price auctions.
Most of the research I've seen around advertising auction types is focused on the Google paid search auction. The common misconception is that the Google exchange is a Vickrey-Clarke-Groves auction, but most experts conclude that it is in fact a generalized second-price auction. Both auctions support some type of price reduction where the winning buyer pays slightly more than the next highest bid.
The Vickrey auction is designed for the single sale of a tangible asset. The expected buyer behavior in this type of auction is for the buyer to bid the known value of what the good is worth to them. This is called the buyer's willingness to pay. This behavior is expected because there is no risk of overpaying since the price is set by the value of the second place bid.
The GSP auction gives price reduction, however, the asset is not a single expiring good but one that is sold multiple times. In the Google paid search auction, the multiple goods are the multiple winners of the auction that are organized by order of ad slot.
Most search marketers know that the ad slot's relative performance is mostly invariant. This means that the performance of ad slot two will be about the same as it is for ad slot one. There are branding reasons to be in ad slot one, but that is a feature that is not given much value by the search buyer, so the "performance" drives the valuation of the search buyer.
The behavior of a buyer in a GSP auction is different than in a Vickrey auction. In a GSP auction a buyer should not bid their willingness to pay but instead just enough to win at least slot three.
In a traditional English auction, commonly called a first-price auction, the winning bidder is the max bidder and they pay what they bid. The expected behavior of the buyer in this type of auction is to bid below the buyer's willingness to pay and just enough to win the auction but as little above the second place bidder as possible. This type of bidding involves a lot of uncertainty that fuels analysis into forecasting, valuation, and gamesmanship where the buyer tries to figure out the value of the asset to all likely bidders.
The English auction and GSP auction both encourage a bidding strategy known as bid shading. This is when the buyer hides their willingness to pay for the asset to avoid paying too much. The more buyer uncertainty of how much to shade the bid, the more likely they are to bid lower than they would if the auction were a Vickrey auction. The end result for the auction is a lower bid average for each ad impression as compared to what the bid average would be if it were a Vickrey auction.
In the real-time bidding (RTB) ad exchanges, each impression has only one winner and there is also price reduction to the second highest bid, so you would expect buyers to bid their willingness to pay like they would in a Vickrey auction. However, there are alternate market dynamics at play that encourage RTB buyers to embrace bid shading.
The New Daisy Chain
Ad exchanges were born to minimize inter-ad network daisy chaining. This was the initial premise behind Right Media Exchange (RMX). What has happened is that participants in ad exchanges and, in some cases the ad exchanges themselves, participate in a form of a super daisy chain across multiple exchanges.
Some exchanges are used more for price skimming and others for fill. More than a year ago we took a measure across exchanges for the difference in our bids vs. the clearing price across different exchanges. When the value gap is skewed to the left the exchange is more likely to act like a first-price auction and warrant bid shading. When there is normal distribution the exchanges are more likely to behave as a second-price auction and encourage willingness to pay bidding.
With such a vast difference it is likely that sellers of Exchange 2 (left skew) are setting floor prices that are in line with our advertisers' bids. When buyers bid less than average the impression leaves Exchange 2 and ends up in a fill exchange (normal distribution) like Exchange 1.
These observations lead our algorithms, our traders, and our advertisers to bid lower or outright block domains/exchange combinations where we observe cross-selling and/or odd behavior.
Over time, the publisher's use of daisy chaining will lead more and more buyers to shade their willingness to pay and create a set of market dynamics that anchor the clearing price of digital media.
More transparent and market-driven exchanges will allow natural buyer competition to reveal an advertiser's willingness to pay and naturally drive up pricing. This is where most analysts feel the RTB marketplace will go once the publishers feel there is enough buyer competition in the marketplace. This is not reality in the current state.
As a representative of the media buyers, I am indifferent as to whether or not publishers truly adopt market-driven pricing. The more games media sellers play, the more advantage buyers who have the data and analytics horsepower to react can and will.
I want to leave this column with a question. There are a lot complex decisions that need to be made inside filtering strategies and algorithms that only a few in the industry truly know. There are different companies in our space. Some that represent buyers, some networks, some trading desks, some sellers. There are also some that say they represent all. Which one represents you?
Bidding image on home page via Shutterstock.
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As the chief operating officer and co-founder of Digilant, Nate oversees the company's day-to-day operations.
Previously Nathan served as senior vice president of Havas Digital's corporate development team. During his tenure he won two Innovation Awards, Advertising Age's Up and Coming Marketer of the Year, Media Week's BestMedia Campaign, and a MIMC award for Best Advertising Campaign ROI Measurement.
Nathan began his career at HookMedia. He received his MBA from Babson Olin School of Management and his BA from Boston College.
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