A case that is seen as a key test of potential antitrust action against Google, with ramifications for similar action against other hyperscale app providers such as Apple, Meta and Amazon, will be decided this year.
The U.S. Justice Department sued Google in U.S. District Court for the District of Columbia, alleging that the company illegally protected its monopoly in internet search, partly by paying billions to persuade companies, including Apple and Samsung, to use its search engine.
But some might argue such deals are not unusual in business. In retail, manufacturers sometimes pay stores "slotting allowances" for prominent shelf placement. This ensures their products are more visible to consumers, potentially increasing sales. Similarly, Google's payment gives it higher visibility on iPhones.
In media, websites might offer premium ad placements for a higher fee. These placements are more likely to be seen by users, potentially driving more clicks and revenue. Google's payment to Apple could be seen as a form of premium placement for its search engine.
Some media outlets publish sponsored content for a fee. Google's prominent placement on iPhones could be viewed as a form of sponsored content, where Apple is "sponsoring" Google Search as the default option.
Cable companies might charge a premium for certain high-value channels to be included in their packages.
But some might argue those analogies do not apply so well. In retail, some might argue, there are typically multiple brands competing for shelf space. Consumers can easily choose alternative products on nearby shelves. On iPhones, changing the default search engine can be cumbersome and some users might not even be aware they can do so.
Others might argue that transparency is an issue. The argument is that slotting allowances and pay-per-click placements are often disclosed, so consumers know a product placement is sponsored.
Likewise, prior precedent will play a key role in determining the outcome.
Case | Year | Court | Key Takeaway | Relevance to Google-Apple Deal |
Microsoft v. US | 1998 | US Court of Appeals | Dominant companies can't unfairly disadvantage competitors. | Supports arguments that Google's payments stifle competition. |
Eastman Kodak Co. v. Image Technical Services, Inc. | 1996 | US Court of Appeals | Dominant companies can't use their power to foreclose competitors from markets. | Supports arguments that Google's deal limits user choice for search engines. |
FTC v. Qualcomm | 2017 | Federal Trade Commission | Tying arrangements where access to one product is conditioned on another can raise antitrust concerns. | Supports arguments that Google's payments create an unfair tie-in between iPhones and Google Search. |
Sun Microsystems, Inc. v. Microsoft Corp. | 1993 | US Court of Appeals | Companies have some freedom to choose what software to integrate. | Could be used by Apple to defend its right to choose a default search engine. |
Verizon Communications Inc. v. FCC | 2012 | Supreme Court | Companies might have more leeway in managing their platforms. | Potentially weakens arguments against exclusive deals on private platforms like iPhones. |
The coming decision hinges on whether Google's payments stifle competition. The judge will have to balance consumer choice and possibly the impact on innovation. Users can change their default browser, though, so the issue is whether such default installs actually reduce competition, or only reinforce user preferences.
According to StatCounter, Google’s Chrome holds about 65 percent of the installed base or share, globally. The argument on one side is that this reflects user preference. The argument on the other side is that such leadership is dependent on tying agreements to some extent.
Browser | Percentage Share | Source |
Chrome | 64.73% | StatCounter |
Safari | 18.56% | StatCounter |
Edge (Microsoft) | 4.97% | StatCounter |
Firefox | 3.36% | StatCounter |
Opera | 2.86% | StatCounter |
Samsung Internet | 2.59% | StatCounter |
Other Browsers | 2.93% (combined) | StatCounter |
But there are many reasons why Google is dominant in search. Google's search algorithm is widely considered the most advanced and effective, delivering relevant and accurate results to users' queries. In other words, users might simply prefer Google because they believe it delivers the best results.
In that regard, extensive troves of data might allow for greater and more effective personalization and search accuracy as well.
Some might point out that Google possesses a vast amount of user data and search history, allowing it to personalize search results and continuously refine its algorithms for better performance. Others might point to global presence; language support and local customization.
Network effects--or possibly simply scale benefits--then also kick in. More users generate more search queries and data, which Google can leverage to improve its search algorithms and personalize results.
A larger user base exposes Google Search to a wider range of searches and information needs, which might arguably help the algorithm identify emerging trends and improve its understanding of user intent.
Still, “network effects” refer to platforms where value grows as the number of users grows. That is not necessarily an advantage for Google search. No single user or query necessarily benefits from all other users in a traditional way.
It might be less clear how the Google ecosystem of products and services (Gmail, Maps, YouTube) contributes to "stickiness,” but some value is to be found there.
Deals with device manufacturers like Apple (to be the default search engine) or browsers like Firefox (to be the default search provider) help by ensuring prominent placement on popular platforms.
Others might point to Google’s ability to keep investing in its product, given its strong revenue position, as well.
The point is that there are all sorts of potential ways Google might benefit from trends that flow from having large market share. But Google arguably only benefits because end users prefer it. Maybe Google search leads simply because users prefer it to other products.
Study Title
| Publication Date
| Publishing Venue
| Key Findings
| Network Effects?
|
Why Google Search Matters: Understanding User Preferences for Leading Search Engines
| 2022
| Journal of the Association for Information Science and Technology
| Examines user preferences and identifies factors like search accuracy, result comprehensiveness, and user interface design as key drivers of Google's market share. | Indirectly explores network effects through the role of data in improving search accuracy.
|
The Google Search Algorithm: A Survey
| 2020
| ACM Computing Surveys
| Analyzes the technical aspects of Google's search algorithm, highlighting its sophistication and ability to handle complex user queries and natural language processing. | Focuses on the technical underpinnings of Google's search advantage, not directly on network effects.
|
The Data Advantage: How Google Uses Big Data to Power Search
| 2021
| Harvard Business Review
| Discusses Google's vast data collection and its role in personalizing search results and improving algorithm performance.
| Argues that data advantage is a key driver of Google's success, potentially linked to network effects through the continuous accumulation of user data. |
The Network Effects of Search Engines: An Economic Analysis
| 2019
| Information Economics and Policy
| Analyzes the network effects concept in search engines, acknowledging the role of data accumulation but suggesting alternative explanations like brand reputation and switching costs. | Provides a critical perspective on the role of network effects in Google's dominance.
|
Search Bias and User Lock-In: An Examination of Google's Search Engine Market Power
| 2023
| Journal of Competition Law & Economics
| Investigates potential anti-competitive practices by Google, raising concerns about lock-in effects that might discourage users from switching to alternative search engines. | Discusses the potential negative aspects of a dominant search engine with a large user base.
|
Also, the search function has broadened over the decades, with different sorts of searches, many related to commerce, now prominent. That might matter if courts have to evaluate search market power. There are more types of search and more providers.
Study Title
| Publication Date | Publishing Venue | Key Findings
| Traditional Search % | Commerce-Related Search % |
Evolving User Search Behavior: A Comparative Analysis of Traditional and Shopping Queries
| 2023
| Search Engine Journal
| Identifies a significant rise in shopping-related queries, with users increasingly starting their product research online. | 62% | 38% |
The Rise of "Buy" Online: How Search Trends are Shaping Consumer Behavior
| 2022
| McKinsey & Company
| Reports a surge in searches combining informational keywords with shopping intent (e.g., "best laptops for students 2024"). | 58% | 42% |
Search Intent: Decoding the Why Behind the What
| 2021
| Moz
| Categorizes search queries by intent (informational, navigational, transactional). While informational searches remain prevalent, transactional searches are steadily growing. | 68% | 32% |
The point is that the search market is broader than it used to be, and Google search is part of that broader market.
Category | Potential Leaders |
Search Engines | Google, Bing |
Shopping Platforms | Amazon, Walmart, eBay |
Social Commerce Platforms | Instagram, Pinterest |
Comparison Shopping Engines | Google Shopping, Shopzilla |
Voice Assistants | Siri (Apple), Alexa (Amazon) |
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