USA v. Google LLC Court Filing, retrieved on January 24, 2023 is part of . You can jump to any part in this filing . This is part 14 of 44. HackerNoon’s Legal PDF Series here IV. GOOGLE’S SCHEME TO DOMINATE THE AD TECH STACK B. Google Uses Its Acquisitions and Position Across the Ad Tech Stack to Lock Out Rivals and Control Each Key Ad Tech Tool 3. Finally, Google Uses Its Control of Publisher Inventory to Force More Valuable Transactions Through Its Ad Exchange 109. Google’s ownership of the leading publisher ad server, DFP, allowed it to set the rules that governed how most publisher inventory in the market is sold. Google internally referred to publisher ad servers as the “ad revenue operating system for publishers” because they decide who is offered a chance to buy publisher inventory and on what terms. Not content to operate in a free and competitive market, Google altered its publisher ad server rules to force more transactions—and more high-value transactions—through its ad exchange and advertiser platforms. The changes did not allow Google’s ad exchange rivals to compete in the same way or on the same terms, largely leaving them with the leftover scraps of inventory that Google’s advertisers did not want, even at artificially discounted prices. 110. Until at least the advent of header bidding between 2012 and 2013 (and for many publishers not until at least 2018), publishers that wanted to offer inventory to multiple ad exchanges via Google’s publisher ad server had to use a system known as the “waterfall.” Even though this system plays a smaller role now than it once did,[12] it played a pivotal role in establishing Google’s dominance in the ad exchange market, was a critical predicate to certain other Google conduct, and helped to create the market monopoly that Google enjoys today. 111. Under the waterfall process, the publisher ad server would send offers to sell advertising inventory to ad exchanges and advertiser ad networks one at a time in sequence until it found an eligible buyer. To set up the waterfall, publishers had to manually enter into the publisher ad server the average price they expected to be paid by each ad exchange based on historical averages. Because these were average prices, they did not necessarily reflect what an ad exchange would pay for any individual impression at any particular time. The publisher ad server then ranked each ad exchange from highest to lowest based on average historical price. Then when a user opened a publisher’s webpage and an ad impression became available for sale, the ad server offered the impression to the ad exchange ranked highest in the waterfall. If that ad exchange had an advertiser willing to pay more for the impression than the minimum price set by the publisher (the “price floor”)—which could differ from the average prices of that ad exchange—the ad exchange won the impression, and its advertiser was able to display the ad. The ad was not submitted to any of the other ad exchanges in the waterfall, even if one of them might have been willing to pay more for the impression. Alternatively, if the first ad exchange did not have an advertiser willing to pay at least the publisher’s price floor, the ad server called the next ad exchange in the list. This process continued until someone purchased the impression or the last ad exchange in the waterfall was called. 112. The inefficiencies associated with the waterfall system are obvious: ad exchanges at the bottom of the waterfall might never get a chance to bid, even if they could supply a lucrative bid. In those instances, publishers received less revenue than they could have. But while this inefficiency plagued how inventory was sold to rival ad exchanges, Google used its control over the process to allow its ad exchange—and only its ad exchange—to compete outside of the waterfall process. 113. As part of its post-acquisition relaunch of AdX, on a “system written from scratch” on Google’s platform, Google redeployed “dynamic allocation.” Dynamic allocation provided AdX a prized position over all other indirect sources of advertising demand, which allowed AdX to both “see more” and “win more” valuable publisher inventory. 114. , Google configured its publisher ad server to afford Google’s ad exchange a “first look” at all inventory the ad exchange was eligible to buy. Google’s publisher ad server always called Google’s ad exchange for a real-time bid before offering inventory to rival ad exchanges. This placed Google’s ad exchange at the top of every waterfall, regardless of where it would otherwise be ranked based on its average historical prices. In practice, it meant that Google’s ad exchange saw more publisher inventory than any other ad exchange and could offer advertisers the ability to obtain the most valuable impressions by simply paying slightly more than a static historical average price paid by rival ad exchanges. First 115. , before Google’s ad exchange competed for an impression, Google’s publisher ad server shared with its ad exchange the highest competing price from the waterfall, i.e., the highest average price of a rival ad exchange. This set the auction floor price within Google’s ad exchange and provided bidders on Google’s ad exchange with two key advantages: (1) buyers on Google’s ad exchange could see the floor price (i.e., the minimum price to win) and adjust their bids accordingly; and (2) buyers on Google’s ad exchange often had to pay only that average price of the rival ad exchange. The latter of these advantages was a function of Google conducting a second-price auction on its ad exchange. Under this auction format, if only one bid on Google’s ad exchange was higher than the price floor, that bid won the inventory at the floor price that had been set by the rival ad exchange’s average price. In this way, Google’s ad exchange was able to win high-value impressions without paying the price advertisers on other ad exchanges were actually willing to pay. Second 116. , Google configured the ad server to allow its ad exchange to compete on the basis of real-time pricing derived from its internal auction for a particular impression shown to a particular internet user. Unlike rival ad exchanges, Google’s ad exchange was not relegated to competing on the basis of historical average prices. Combined with Google’s treasure trove of user targeting and webpage contextual data, Google’s control over the ad server allowed it to tailor its bids more carefully; that is, it could bid high for a more valuable impression and low for a less valuable impression. For example, it could offer a publisher $10 CPM to show a car dealer’s advertisement to a user who recently clicked through several car manufacturer websites while offering the same publisher only $1 CPM to show the same ad to a 14-year-old user who resides in a state where the dealer does not operate. Google’s publisher ad server would not permit other ad exchanges to compete in this way. Instead, all other ad exchanges were forced to compete on the basis of the “waterfall” method using historical, average prices, even though the industry quickly developed a technology standard to bid in real time in this way. Third 117. This two-tiered arrangement denied rival ad exchanges the opportunity to gain the scale needed to compete effectively with Google by diverting bidding opportunities and transactions to Google’s ad exchange and away from rivals who did not have a chance to compete at all or to compete on the same terms. It also harmed publishers in the form of lower revenues, limited the ability of advertisers to identify publisher inventory they valued most at the best prices, and decreased the overall quality of matches between publishers and advertisers. 118. Under the waterfall setup, rival ad exchanges never had the opportunity to bid on most impressions. If an ad exchange earlier in the waterfall sequence submitted a bid above the publisher’s price floor, the ad server never offered the inventory to ad exchanges lower in the waterfall. The rules that Google’s publisher ad server applied to Google’s ad exchange, however, provided Google’s ad exchange the opportunity to bid on every eligible impression, armed with substantial data on the publisher’s inventory and the competitive landscape. Because rival ad exchanges were relegated to the waterfall process, unlike Google’s ad exchange, they had limited windows into the universe of publisher inventory available and lacked the valuable data on available inventory and competition that Google harvested. By preventing publishers from freely multi-homing and seeing real-time bids from multiple ad exchanges, Google deprived publishers of the benefits of full competition between ad exchanges. Likewise, by providing Google’s ad exchange with a preferential—and for many impressions, sole—opportunity to buy publisher inventory, Google discouraged advertisers from multi-homing among ad exchanges and provided a substantial competitive advantage to buyers on Google’s ad exchange, the largest buyer being Google Ads. 119. In addition, through dynamic allocation, Google’s ad exchange had the opportunity to win impressions whenever it matched a rival’s average price. This permitted Google’s ad exchange (and its largest buyer, Google Ads) to win more impressions than its rivals, especially higher-value impressions. But for dynamic allocation, a rival ad exchange might have won the impression because it could offer a higher price or better match. Over time, this distortion of the auction process meant that advertisers were more likely to win the impressions they most wanted through Google’s ad exchange as compared to a rival ad exchange. As a result, rival exchanges struggled to attract advertiser ad campaigns, which in turn made it difficult for them to amass publishers willing to offer their inventory through the ad exchange. Of course, dynamic allocation also hurt Google’s own publishers, by sacrificing the fees they paid Google to maximize the value of their advertising inventory. 120. In 2014, Google expanded and further entrenched its artificial advantages by introducing “enhanced” dynamic allocation, which remains in place today. This update allowed Google’s ad exchange to obtain the benefits of dynamic allocation over inventory potentially covered by direct contracts between publishers and advertisers. Historically, this inventory was not offered to ad exchanges at all because qualifying inventory was set aside to fill the direct contract; only after the direct contract was filled did otherwise qualifying inventory become available for auction. Enhanced dynamic allocation afforded Google’s ad exchange a right of first refusal over this inventory regardless of whether the publisher had yet fulfilled the terms of the direct contract. Enhanced dynamic allocation allowed Google’s ad exchange to win the impression as long as it was willing to pay more than Google’s own estimate of the “value” of fulfilling the terms of the direct contract at that moment, which Google calculated through an opaque process that predicted the likelihood the publisher would still be able to satisfy the terms of the direct contract through future impressions even if Google’s exchange filled the one currently available. At the same time, Google ensured that “[i]t [was] not possible for publishers . . . to deactivate Enhanced Dynamic Allocation” within the publisher ad server. 121. Combined, dynamic allocation and enhanced dynamic allocation push more transactions through Google’s ad exchange by unfairly tilting the playing field in Google’s favor, driving additional scale benefits available only to Google. Because of the exclusive link between Google’s ad exchange and its market-leading publisher ad server, no rival can offer publishers or advertisers the same terms as Google. The benefits to Google, and only Google, are plain. 122. , Google has been able to apply its substantial 20% revenue share fee at the ad exchange level over more transactions, boosting Google’s revenues and profits. This fee has been earned not only on transactions where Google Ads won, but also on transactions where other Google and non-Google advertiser buying tools won. Because Google could capture these higher revenues at the ad exchange level, Google was able to forgo or heavily discount the fees it otherwise might charge for publisher ad server services—historically much smaller than ad exchange fees. Indeed, for many customers, Google completely waived publisher ad server fees on a given transaction if it was able to charge its 20% ad exchange fee. By extracting higher fees at the ad exchange level than at the publisher ad server level—which Google needed to control to force more transactions to its ad exchange—Google has also able to maintain low ad serving fees while still achieving its margin goals across the ad tech stack. This fee structure discourages entry by potential ad server competitors, because entry could only be economically feasible by replicating Google’s overall strategy: building dominant positions at each level of the ad tech stack and forcing more transactions to flow through those tools. First 123. , by forcing more transactions through Google’s ad exchange and away from rivals, Google has distorted the pathways through which publishers and advertisers transact and impeded the ability of competitors to gain the scale necessary to compete effectively in the ad exchange market. Google’s dynamic allocation and enhanced dynamic allocation programs have decreased the likelihood that a rival ad exchange could win a transaction, even if it had an advertiser willing to pay the most for an impression. In turn, this has diminished the ability of ad exchanges to attract additional publishers and advertisers to their platforms and has deprived them of valuable transaction data that could improve their competitiveness. Second 124. , by giving Google’s ad exchange (and only Google’s ad exchange) a “first look” option of purchasing publisher impressions offered for sale through DFP, Google has limited the ability of publishers to freely and effectively offer their impressions for sale on multiple ad exchanges. Dynamic allocation and enhanced dynamic allocation has resulted in a two-tiered system—a special auction where Google’s AdX competed and a secondary, inferior auction potentially available to rival exchanges. Publishers are unable to partner with Google’s rival ad exchanges on the same terms as Google’s AdX. Those rivals cannot integrate with DFP via a mechanism equivalent to dynamic allocation, even if they had the technological capability to do so. Third 125. Even though Google modified the way dynamic allocation operated in late 2019, the effects of the decade-long program persist. Over that period, Google has amassed substantial scale within its ad exchange while undercutting rivals’ ability to do the same. The flywheel network effects of that scale continue to advantage Google’s ad exchange, especially when combined with the new algorithmic bidding programs described below that largely replicated the effect of dynamic allocation. Even today, Google continues to use enhanced dynamic allocation to favor buyers transacting through Google’s platforms. Only those buyers can bid with knowledge of the Google-determined price floor that Google sets through enhanced dynamic allocation. [12] Because of the difficulties and costs of utilizing newer alternative systems in Google’s ad server, many publishers are still forced to use the waterfall system today. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 1:23-cv-00108 retrieved on September 8, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. justice.gov

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