Google is a monopoly: Key Learnings Pt 2
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This post continues last week’s, in which I discussed the high-level background of the antitrust decision that declared Google a monopoly.
This week’s post will summarize my most interesting learnings and insights from the 286-page document. I read it, so you don’t have to, but here is my highlighted document if you want to read it yourself.
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The details are below, complete with quotes from the verdict, but I will put the TL;DR at the top. There are great general articles on the verdict, but these are my most interesting takeaways.
Google is as dominant in search as everyone thinks it is: It has 89.4% of the total search market, which climbs to 94% on mobile.
It will be tough for a new search engine—even one as popular as ChatGPT—to take search share from Google even with a better product. People Google out of habit.
Google does not consider any other search engine a competitor, but it does view social media and vertical search engines like Amazon as competition.
Bing is as good as Google, but it can’t break through because of habits and Google’s default relationships.
Neeva and DuckDuckGo also felt like they had great products but couldn’t attract users for the same reasons.
Google’s default relationships with Apple and others allowed it to become the Google of today; without them, another engine might have been able to grow.
Google pays Apple, but Apple would likely still use Google as the default search engine even if they wouldn't.
Most users search through a default like Chrome or Safari and don’t go to Google.com.
How Google works (specifically from the verdict.)
Google uses AI to understand the intent of queries
Google then classifies all queries by a vertical
Google decides which queries deserve freshness and which websites need to be refreshed. This is a hint of a crawl budget.
User data is Google's most powerful weapon, and according to the verdict, this feedback loop keeps Google ahead of every other entrant.
According to Google and the court, we are still in the early days of AI, and LLM’s will not replace search.
Google used its monopoly power to raise prices on advertisers, and when it conducts pricing tests, it doesn’t consider that advertisers may flock to a competitor.
Conclusion of this TL;DR
For marketers, I don’t think anything will change regardless of how the court penalizes Google. Google will remain the most dominant search engine because of its superior products and user habits.
Additionally, based on the verdict's reading, I don’t believe any of the parties to this trial thought that LLMs were a serious risk to Google, which means that Google search will remain the most dominant force in search marketing.
The verdict makes for interesting reading. The court deeply understood how algorithms work to rank search results, and again, I think the full document makes for a great read.
As an example, this graphic included in the verdict shows this level of complexity:
And one teaser from the document that I just had to include in this TL;DR:
Pertinent paragraphs supporting the above conclusions are below.
Google’s Market share
There was no clear indication of Google’s total market share for years. Most SEOs believed Google to be higher than 90% of search share (dependent on vertical, of course) because that’s what they saw in their analytics tools. However, this was a number that Google never shared publicly, and Bing always obscured. This opacity served Google because if they hadn’t been perceived to be as dominant as they were, it might have kept the DOJ at bay, and Microsoft didn’t want advertisers to know how small they indeed were. Now, as a result of this verdict, we know:
Measured by query volume, Google enjoys an 89.2% share of the market for general search services, which increases to 94.9% on mobile devices. FOF ¶¶ 23–24. This overwhelms Bing’s share of 5.5% on all queries and 1.3% on mobile, as well as Yahoo’s and DDG’s shares, which are under 3% regardless of device type.Who competes with Google for real
In past posts, I have suggested that Google should be more concerned about its big tech competitors (Apple, Amazon, Meta) than startups taking market share from them. The verdict supports this idea, as we now know that Apple has an index of websites but doesn’t currently use it. Generally, constructing a search engine is highly capital-intensive, which is likely why startups will not succeed.
Google “estimate[d] that the total capital expenditures required [for Apple] to reproduce [Google’s technical] infrastructure dedicated to search would be in the rough order of $20[ billion].” UPX2 at 392–93; Tr. at 1644:8-20 (Roszak). Google further estimated that, if Apple needed only half of Google’s infrastructure to produce a competitive GSE, it would have to spend $10 billion to get it off the ground, plus $4 billion annually in technical infrastructure. UPX2 at 393. On top of that, if Apple could sustain a business with only one third of Google’s engineering and product management costs, it still would cost Apple $7 billion annually. Seven billion dollars was equal to more than 40% of Apple’s total research and development expenditure in 2019. Id.The force of habit that keeps people Googling
Another reason startups would have difficulty succeeding in blunting Google is that it is a habit. User gravitation to Google is out of a force of habit.
According to U.S. Plaintiffs’ expert, Dr. Antonio Rangel, whose testimony the court credits, “the vast majority of individual searches, or queries, are carried out [by] habit,” because search is a high frequency activity done on a familiar device that provides an instant response. Id. at 543:2-9 (Rangel) (“Habits develop very strongly in those situations of high repetition and immediate feedback.”); see also id. at 543:14-19 (Rangel) (“When a consumer encounters their devices for the first time and they start searching, they start searching with the default search engine, which for many of them is the case. . . . If that search engine that is the default generates adequate experiences, the consumer will get habitized to that.”). A 2020 Google study confirmed this. A group of iOS users were asked what app they would choose to open a link in an email: Chrome, the Google Search app, or Safari? Regardless of the option the user selected, their leading rationale for doing so was “Habit/Regular Usage.” UPX757 at 628.People tend to stick with the status quo, as it takes more effort to make changes.” UPX103 at 214; see also UPX171 at 190 (2015 Google study based on 26 user interviews; almost half of the users (12) did not notice a surreptitious change from Google to Bing on their iPhone; “People expressed interest (but not huge urgency) to switch back to Google”); Tr. at 7677:5– 7682:19 (Pichai) (discussing UPX172, a 2005 letter from Google to Microsoft stating that “most end users do not change defaults”).The amount of choice friction varies and depends on many factors. For instance, default effects are weaker when the product is of poor quality or is unknown to users. Consumers “start thinking about switching more if the experience is unsatisfactory” or if they have, “over years, developed a very strong preference for a [rival] brand[.]” Id. at 548:15-20 (Rangel). By contrast, default effects are stronger when the user is satisfied with the product. Id. at 650:22– 651:9 (Rangel).In a 2016 experiment, Mozilla switched the default GSE on both new and existing users from Google to Bing. By the twelfth day, Bing had kept only 42% of the search volume. DX679 at .006. After some additional time, those numbers dropped to 20–35%, depending on certain variables. Id. Mozilla’s takeaway was that switching the Firefox default to Bing would result in missing revenue targets. Id.Brought to you by North Star Inbound—the sales enablement SEO agency.
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The power of Google’s default relationships
In addition to habit, which is the whole point of the DOJ’s suit, most users are accessing Google via a default relationship, whether on Apple or in a browser. A startup would have to supplant Google in a default relationship, something Neeva and DuckDuckGo could never do.
Only 30% of search runs through an access point that’s not Google Thus, only 30% of queries in the United States run through a search access point that does not default to Google. See id. at 5762:22–5763:13 (Whinston) (discussing UPXD104 at 37). (To be clear, those 30% of searches are not all run on GSEs other than Google. A large percentage of those searches still are entered into Google, but through channels other than the default search access points, such as user-downloaded Google Search app or a search on www.google.com.The risk to Google from losing those defaults
Obviously, these defaults are incredibly important and valuable to Google, and this is precisely where the monopoly comes in.
In 2020, Google’s internal modeling projected that it would lose between 60– 80% of its iOS query volume should it be replaced as the default GSE on Apple devices, UPX148 at 826, which would translate into net revenue losses between $28.2 and $32.7 billion (and over double that in gross revenue losses), UPX1050 at 887. And in a 2015 presentation, Google expressed confidence in its standing among Apple users, but warned that its position “is still very vulnerable if defaults were to change.” UPX171 at 186Google has long recognized that, if Apple were to develop and deploy its own search engine as the default GSE in Safari, it would come at great cost to Google. See generally UPX2. See Tr. at 7693:12–7697:12 (Pichai); id. at 8094:11–8096:4 (Gomes). For example,Google projected that without the ISA, it would lose around 65% of its revenue, even assuming that it could retain some users without the Safari default. See UPX1050 at 886.Neeva insists that they had a great [product, but they weren’t successful because of Google default agreements.
The reason “why Neeva failed . . . was simply because [it] could not get enough users to be in that state where they regularly used Neeva.” Id. at 3712:10-12 (Ramaswamy); id. at 3677:2-3, 3700:25–3701:7 Apple extorts Google
Given that Apple would never use Bing, Google is still forced to pay them a rev share.
Although Apple has never seriously considered Bing as an option, Microsoft perceives that Apple has used Bing “to bid up the price” in its negotiations with Google and extract a higher revenue share from Google. Id. at 3505:6 (Nadella). Microsoft CEO Satya Nadella testified that if, hypothetically, Bing exited the market, there would be a real concern as to whether Google would even pay Apple for default status, given the lack of any other option at all. Id. at 3505:12-17 (Nadella).When the court asked why Google pays billions in revenue share when it already has the best search engine, he answered that the payments “provide an incredibly strong incentive for the ecosystem to not do anything”; they “effectively make the ecosystem exceptionally resist[ant] to change”; and their “net effect . . . [is to] basicallyMost users come through these default relationships and
Google recognizes that the user-downloaded GSA is an ineffective way to reach users. A 2018 internal study revealed that over 35% of iOS users did not know they could download GSA, and most of those who were aware of GSA did not want to install it. See UPX139 at 149. Over half of Safari users had not installed GSA, and of those that had installed it, over 80% still preferred using Safari. Id. at 150.Alternative browsers are not a threat to Google
Users also can reach GSEs by downloading an alternative browser from an applications store or the web. For example, a user can download Chrome, Edge, or DDG onto an Apple device. This, too, is not an easily accessible search point, as it involves similar choice friction as acquiring a search application. Google receives only 7.6% of all queries on Apple devices through user-downloaded Chrome. Id.On such devices, Edge is the default browser and Bing is the default search engine. Id. at 3096:14-20 (Tinter). Yet, Google’s search share on Windows devices is 80%, with most of the queries flowing through the Chrome default, which means Chrome was downloaded onto the device. See id. at 9737:9-21 (Murphy) (discussing DXD37 at 36, 38). Google’s dominance on Windows cannot, however, be attributed simply to the popularity of Chrome. Google had an 80% search share on Windows when Chrome first launched, and that share has remained steady ever since (see below).MS Edge shows the power of defaults
The power of defaults is evident, however, from the share of Bing users on Edge. Bing’s search share on Edge is approximately 80%; Google’s share is only 20%. Id. at 5744:24– 5745:20 (Whinston) (discussing UPXD104 at 29). Even if one assumes that some portion of those Bing searches are performed by Microsoft-brand loyalists, Bing’s uniquely high search share on Edge cannot be explained by that alone. The default on Edge drives queries to Bing.User data is Google’s most powerful weapon
Greater query volume means more user data, or “scale.” As the most widely used GSE in the United States, Google receives nine times more queries each day than all of its rivals combined across all devices. The disparity is even more pronounced on mobile. There, Google receives nineteen times more queries than all of its other rivals put together. See Tr. at 4761:6-24, 4762:19–4763:2 (Whinston) (discussing UPXD102 at 47, 49).Google’s scale means that it not only sees more queries than its rivals, but also more unique queries, known as “long-tail queries.” To illustrate the point, Dr. Whinston analyzed 3.7 million unique query phrases on Google and Bing, showing that 93% of unique phrases were only seen by Google versus 4.8% seen only by Bing. On mobile, where Google has more scale, the disparity was even higher. See id. at 5785:12– 5788:1 (Whinston) (98.4% of unique phrases seen only by Google, 1% by Bing; 99.8% of tail queries on Google not seen at all by Bing) (discussing UPXD104 at 44).Even if Google’s modern data-based signals yield identical results when trained on a fraction of their scale, Google’s ability to design and engineer those signals relied on volumes of user data that Bing (nor anyone else) has never had. FOF ¶¶ 98, 105; Tr. at 10318:9-24 (Oard) (“[T]hat’s the way Google does it is based in part on Google seeing what works and trying out new ideas, and user-side data is just all over that process. And so that if you have access to more and better user-side data, then you have opportunities to do things here you might not otherwise have. And that’s simply not measured in the experiment, right. That experiment of this general design couldn’t possibly measure that effect. I mean, you’d have to replay 20 years of search engine development.”).User data helps determine which sites to crawlDr. Fox concluded that only 2.9% of the quality gap between Google and Bing was attributable to their respective volumes of user interaction data. Tr. at 7848:18-24 (Fox) (discussing DXD26 at 10); see GFOF ¶¶ 382–386, 349.The court found Dr. Fox’s experiment to be an interesting exercise but ultimately is unpersuaded by it. If Dr. Fox is right that Google could operate a search engine of equal quality using the amount of data possessed by Bing, one would expect Google to have used the experiment beyond just litigation.AI decreases the reliance on user data, but it will never go to zero
More recent ranking signals developed by Google rely less on user data. Those include RankBrain, DeepRank, RankEmbed, RankBERT, and MUM. See UPX255 at .010; UPX2034. Known as “generalization” systems, these signals “may not be so good at memorizing facts, but they’re really good at understanding language.” Tr. at 1846:18-22 (Lehman). Such systems are “designed to fill holes in [click] data”; they allow Google to generalize from situations where it has data to situations it does not. Id. at 1896:2-19 (Lehman).More recent ranking signals developed by Google rely less on user data. Those include RankBrain, DeepRank, RankEmbed, RankBERT, and MUM. See UPX255 at .010; UPX2034. Known as “generalization” systems, these signals “may not be so good at memorizing facts, but they’re really good at understanding language.” Tr. at 1846:18-22 (Lehman). Such systems are “designed to fill holes in [click] data”; they allow Google to generalize from situations where it has data to situations it does not. Id. at 1896:2-19 (Lehman).Google continues to maintain significant volumes of data—despite the expense of storing it—because its value outweighs that cost. See id. at 6337:17-25 (Nayak) (“[A]s you get more data, it’s more expensive to process.”); id. at 10349:24–10350:7 (Oard) (“[T]he cost of keeping and using this data goes up with the amount of data that we keep. The value goes up as well. And at some point, if the value were to decline to the point where it wasn’t worth the cost, people would stop doing it[.] . . . [T]here’s a sweet spot where you would stop doing it, and Google hasn’t stopped doing it yet.”); id. at 10079:9-10 (Murphy) (“I would presume if they maintain it and it’s costly to maintain it, there’s a reason they maintain it.”).For GSEs with little scale, even a small amount of data can result in meaningful improvements. Id. at 10347:7-10 (Oard) (“And when you have very little, then not only do you get better, but you keep getting better at a faster and faster rate up to some point where the rate at which you’re getting better starts to slow down.”); id. at 2047:21–2048:3 (Weinberg) (“[W]e lack the scale to do as much experimentation as we want[.]”).Google believes we are in the early days of search relative to AI
For GSEs with little scale, even a small amount of data can result in meaningful improvements. Id. at 10347:7-10 (Oard) (“And when you have very little, then not only do you get better, but you keep getting better at a faster and faster rate up to some point where the rate at which you’re getting better starts to slow down.”); id. at 2047:21–2048:3 (Weinberg) (“[W]e lack the scale to do as much experimentation as we want[.]”).User data will always be requiredThis is in part because “deep learning systems are much harder to understand.” Id. at 6366:21-22 (Nayak). It thus remains vital for Google to “have an infrastructure that [it] understand[s],” i.e., traditional ranking signals. Id. at 6366:21–6367:10 (Nayak) (“[T]here is no sense in which we have turned over our ranking to these systems. We still exercise a modicum of control over what is happening and an understandability there.”).Second, the advent of artificial intelligence (AI) has not sufficiently eroded barriers to entry—at least not yet. New technologies may lower, or even demolish, barriers to entry, but such innovation is meaningful only if it can change the market dynamic in the “foreseeable future.” Microsoft, 253 F.3d at 55 (“[W]ere middleware to succeed, it would erode the applications barrier to entry. . . . [But] middleware will not expose a sufficient number of APIs to erode the applications barrier to entry in the foreseeable future.”). Currently, AI cannot replace the fundamental building blocks of search, including web crawling, indexing, and ranking. FOF ¶¶ 114–115. Neeva’s experience is again illustrative. Despite building a search engine enhanced by AI technology, FOF ¶¶ 110–111, Neeva could not ride it to market success. AI may someday fundamentally alter search, but not anytime soon. FOF ¶¶ 114–115.Google considers search quality in product decisions but does not ever fear users going to another search engine
Google does not, however, consider whether users will go to other specific search providers (general or otherwise) if it introduces a change to its Search product.” UPX6019 at 365– In 2020, Google assessed the impact of degrading aspects of its search quality for about three months, specifically its large ranking components (e.g., Navboost, Synonyms). See UPX1082 at 294. The experiment tested a quality decline of 1 IS point, a measure of search quality equivalent to the loss of two times the information contained on all of Wikipedia. See id.; Tr. at 6323:12-17 (Nayak) (“If we took Wikipedia out of our index, completely out of our index, then that would lead to an IS loss of roughly about a half point.”); id. at 4771:4–4773:9 (Whinston) (describing this experiment). This quality-reduction experiment correlated with only a 0.66– 0.99% decline in global search revenue. UPX1082 at 294. In short, this study demonstrates that a significant quality depreciation by Google would not result in a significant loss of revenues. See id. But see id. at 6329:22-25 (Nayak) (“[I]f you made much larger IS changes, the relationship might not stay linear. It might become nonlinear. There might be inflection points where if you make search much worse, for example, you might actually lose a lot more traffic[.]”).Google is afraid of TikTok
63% reported that they use TikTok as a search engine. DX241 at .032. And a 2015 Google User Experience Research study concluded that Google users frequently used specialized vertical providers’ mobile applications. See DX62A at .027–.028.The court did not believe this to be compelling enough:
The evidence does not show, however, that increased use of social media corresponds to a decrease in use of Google. In fact, a 2009 Google study showed that users who increase their use of Facebook tend to use Google more often, not less. UPX902 at 020.Nor did they think social media diminished the monopoly
But Google’s focus on ROI misses the forest for the trees. Products are reasonably interchangeable only if “significant” substitution occurs in response to a price increase. See Ohio v. Am. Express Co., 585 U.S. 529, 543–44 (2018). To be sure, advertisers did testify to shifting spend to maximize ROI. But none said that they have “significantly” shifted ad spend away from search ads. In fact, the opposite is true. Advertisers uniformly said that they would not substitute search ads for another ad type absent some campaign-level reason to do so.Google uses monopoly to increase prices
The evidence does not show, however, that increased use of social media corresponds to a decrease in use of Google. In fact, a 2009 Google study showed that users who increase their use of Facebook tend to use Google more often, not less. UPX902 at 020.In fact, after squashing, Google displayed the same ads on about 95% of queries measured by impressions and clicks, generating 88% of its revenue from queries returning the same ads in the top placement. UPX442 at 872. In other words, the overwhelming majority of revenues resulted from the same placements before and after squashing. Moreover, Google measured success not based on improved ranking for smaller advertisers, but by whether a “squashed” auction produced positive revenues for Google. In one record, Google described squashing as “desirable” when CPCs increased, and “undesirable” when they did not due to “reranking.” UPX737 at 464. Because squashing produced desirable results 60% of the time, Google believed that “coarse squashing provide[d] overall positive metrics” but was “suboptimal due to these mixed effects.” Id. Google proposed to further refine squashing to optimize revenues. Id. at 464–65.Google also reduced advertisers’ ability to remove themselves from certain adauctions by expanding its “keyword matching” functionality. “[T]he typical way that advertisers interact with search advertising is using keywords, which is literally the advertiser [] guessing what the users might be querying, which is very complex. And so doing that for millions of products is sort of an undue burden on advertisers so [Google] came up with an automated system where [it] do[es] more of the matching.” Id. at 1353:21–1354:2 (Dischler).Google also considers vertical search engines like Amazon to be a competitor
Google views competition from SVPs as “intense for commercial clicks.” UPX343 at 845. A 2020 Bank of America study reported that 58% of users search Amazon first when they seek to make an online purchase, as opposed to only 25% who go first to Google, demonstrating Google’s secondary status as a starting point for users with high commercial intent. Tr. at 8425:15–8426:8 (Israel) (discussing DXD29 at 28). Google thus perceives Amazon as posing a risk of siphoning queries away from Google. DX126 at .019.Conclusion on monopoly
It is sufficient at this point to observe what is undisputed, which is that Google does not consider competitors’ pricing when it sets text ads prices.That Google makes changes to its text ads auctions without considering its rivals’ prices is something that only a firm with monopoly power is able to do. And, as will bediscussed, Google in fact has profitably raised prices substantially above the competitive level.Google claims that it “has repeatedly outcompeted its rivals . . . on the basis of its superior quality and monetization,” and that any “scale benefits achieved from winning customers’ business based on competition on the merits [do not] turn[] an otherwise lawful agreement into an unlawful one.”In a sense, Google is not wrong. It has long been the best search engine, particularly on mobile devices. FOF ¶¶ 126–127. Nor has Google sat still; it has continued to innovate in search. FOF ¶ 128. Google’s partners value its quality, and they continue to select Google as the default because its search engine provides the best bet for monetizing queries. FOF ¶¶ 126, 133. Apple and Mozilla occasionally assess Google’s search quality relative to its rivals and find Google’s toBut these largely undisputed facts are not inconsistent with possessing and exercising monopoly power. Nor do they tell the full story. There is no genuine “competition for the contract.” Google has no true competitor. Consider that Google’s monopoly in general search has been remarkably durable. Its market share in 2009 was nearly 80%, and it has increased since then to nearly 90% by 2020. FOF ¶ 23. Bing, during that same period, has never held a market share above 11%, and today it stands at less than 6%—meaning that Google’s biggest rival trails in market share by a whopping 84%. FOF ¶ 25. Yahoo, long ago considered Google’s closest competitor, today holds less than 2.5% of the market. Id. Thus, over the last decade, Google’s grip on the market has only grown stronger.One of them is no longer in business (Neeva), and the other has achieved a market share of 2.1%