Google Found in Violation of Antitrust Law, Judge Rules via @sejournal, @MattGSouthern

A federal judge has ruled that Google violated U.S. antitrust law by illegally maintaining monopolies in the markets for general search services and general search text advertising.

Judge Amit P. Mehta of the U.S. District Court for the District of Columbia, ruling in a case brought against Google by the Justice Department, said that Google had abused its monopoly power over the search business in part by paying companies to present its search engine as the default choice on their devices and web browsers.

Judge Mehta wrote in his opinion filed Monday:

“After having carefully considered and weighed the witness testimony and evidence, the court reaches the following conclusion: Google is a monopolist, and it has acted as one to maintain its monopoly. It has violated Section 2 of the Sherman Act.”

The court found that Google abused its dominant position in several ways:

• Paying hefty sums to ensure default status on devices and browsers
• Leveraging user data to reinforce its search engine’s dominance
• Illegally protecting its monopoly over search-related advertising

Key Findings Of Anticompetitive Behavior

The judge found that Google’s agreements with Apple, Mozilla, and Android partners foreclosed about 50% of the search market and 45% of the search advertising market from rivals.

These exclusive distribution agreements deprived competitors like Microsoft’s Bing of the scale needed to compete with Google in search and search advertising.

Judge Mehta concluded that Google’s conduct had anticompetitive effects:

• Foreclosing a substantial share of the market
• Depriving rivals of scale needed to compete
• Reducing incentives for rivals to invest and innovate in search

The case began in 2020 and culminated in a 10-week trial last fall.

Financial Revelations

The trial disclosed financial details of Google’s default search agreements.

In 2022, Google paid Apple $20 billion for default search placement on iOS devices, an increase from $18 billion in 2021.

Additionally, Google shares 36% of Safari’s search ad revenue with Apple.

These figures highlight the value of default search positioning in the industry.

Google’s Defense & Market Share

Throughout the trial, Google maintained that its market dominance resulted from superior product quality rather than anticompetitive practices.

The company disputed the DOJ’s estimate that it held a 90% share of the search market, arguing for a broader definition of its competitive landscape.

However, Judge Mehta rejected this defense:

“Google has thwarted true competition by foreclosing its rivals from the most effective channels of search distribution.”

Ruling On Search Advertising

On search advertising, the judge found Google could charge supra-competitive prices for text ads without rivals’ constraints.

However, the judge ruled in Google’s favor on some claims, finding Google doesn’t have monopoly power in the broader search advertising market.

Potential Ramifications

While Judge Mehta has yet to determine specific remedies, the ruling opens the door to potentially far-reaching consequences for Google’s business model. Possible outcomes could include:

• Forced changes to Google’s search operations
• Divestiture of specific business segments
• Restrictions on default search agreements

The decision is likely to face appeals, and the final resolution may evolve, as seen in the Microsoft antitrust case of the 1990s.

Broader Context

This ruling sets a precedent that could influence other ongoing antitrust cases against tech giants like Amazon, Apple, and Meta.

It signals a shift in how century-old antitrust laws are applied to modern digital markets.

What’s Next

Google is expected to appeal the decision, potentially leading to a protracted legal battle that could shape the future of online search and digital advertising.

The Department of Justice and a group of attorneys general from 38 states and territories, who filed similar antitrust suits against Google in 2020, will eagerly anticipate the next steps in this legal battle.

Featured Image: Sergei Elagin/Shutterstock

Google Gives 5 SEO Insights On Google Trends via @sejournal, @martinibuster

Google published a video that disclosed five insights about Google Trends that could be helpful for SEO, topic research and debugging issues with search rankings. The video was hosted by Daniel Waisberg, a Search Advocate at Google.

1. What Does Google Trends Offer?

Google Trends is an official tool created by Google that shows a representation of how often people search with certain keyword phrases and how those searches have changed over time. It’s not only helpful for discovering time-based changes in search queries but it also segments queries by geographic popularity which is useful for learning who to focus content for (or even to learn what geographic areas may be best to get links from).

This kind of information is invaluable for debugging why a site may have issues with organic traffic as it can show seasonal and consumer trends.

2. Google Trends Only Uses A Sample Of Data

An important fact about Google Trends that Waisberg shared is that the data that Google Trends reports on is based on a statistically significant but random sample of actual search queries.

He said:

“Google Trends is a tool that provides a random sample of aggregated, anonymized and categorized Google searches.”

This does not mean that the data is less accurate. The phrase statistically significant means that the data is representative of the actual search queries.

The reason Google uses a sample is that they have an enormous amount of data and it’s simply faster to work with samples that are representative of actual trends.

3. Google Cleans Noise In The Trends Data

Daniel Waisberg also said that Google cleans the data to remove noise and data that relates to user privacy.

“The search query data is processed to remove noise in the data and also to remove anything that might compromise a user’s privacy.”

An example of private data that is removed is the full names of people. An example of “noise” in the data are search queries made by the same person over and over, using the example of a trivial search for how to boil eggs that a person makes every morning.

That last one, about people repeating a search query is interesting because back in the early days of SEO, before Google Trends existed, SEOs used a public keyword volume tool by Overture (owned by Yahoo). Some SEOs poisoned the data by making thousands of searches for keyword phrases that were rarely queried by users, inflating the query volume, so that competitors would focus on optimizing on the useless keywords.

4. Google Normalizes Google Trends Data?

Google doesn’t show actual search query volume like a million queries per day for one query and 200,000 queries per day for another. Instead Google will select the point where a keyword phrase is searched the most and use that as the 100% mark and then adjust the Google Trends graph to percentages that are relative to that high point. So if the most searches a query gets in a day is 1 million, then a day in which it gets searched 500,000 times will be represented on the graph as 50%. This is what it means that Google Trends data is normalized.

5. Explore Search Queries And Topics

SEOs have focused on optimizing for keywords for over 25 years. But Google has long moved beyond keywords and has been labeling documents by the topics and even by queries they are relevant to (which also relates more to topics than keywords).

That’s why in my opinion one of the most useful offerings is the ability to explore the topic that’s related to the entity of the search query. Exploring the topic shows the query volume of all the related keywords.

The “explore by topic” tool arguably offers a more accurate idea of how popular a topic is, which is important because Google’s algorithms, machine learning systems, and AI models create representations of content at the sentence, paragraph and document level, representations that correspond to topics. I believe that’s what is one of the things referred to when Googlers talk about Core Topicality Systems.

Waisberg explained:

“Now, back to the Explore page. You’ll notice that, sometimes, in addition to a search term, you get an option to choose a topic. For example, when you type “cappuccino,” you can choose either the search term exactly matching “cappuccino” or the “cappuccino coffee drink” topic, which is the group of search terms that relate to that entity. These will include the exact term as well as misspellings. The topic also includes acronyms, and it covers all languages, which can be very useful, especially when looking at global data.

Using topics, you also avoid including terms that are unrelated to your interests. For example, if you’re looking at the trends for the company Alphabet, you might want to choose the Alphabet Inc company topic. If you just type “alphabet,” the trends will also include a lot of other meanings, as you can see in this example.”

The Big Picture

One of the interesting facts revealed in this video is that Google isn’t showing normalized actual search trends, that it’s showing a normalized “statistically significant” sample of the actual search trends. A statistically significant sample is one in which random chance is not a factor and thus represents the actual search trends.

The other noteworthy takeaway is the reminder that Google Trends is useful for exploring topics, which in my opinion is far more useful than Google Suggest and People Also Ask (PAA) data.

I have seen evidence that slavish optimization with Google Suggest and PAA data can make a website appear to be optimizing for search engines and not for people, which is something that Google explicitly cautions against. Those who were hit by the recent Google Updates should think hard about the implications of what their SEO practices in relation to keywords.

Exploring and optimizing with topics won’t behind statistical footprints of optimizing for search engines because the authenticity of content based on topics will always shine through.

Watch the Google Trends video:

Intro to Google Trends data

Featured Image by Shutterstock/Luis Molinero

Google Confirms Robots.txt Can’t Prevent Unauthorized Access via @sejournal, @martinibuster

Google’s Gary Illyes confirmed a common observation that robots.txt has limited control over unauthorized access by crawlers. Gary then offered an overview of access controls that all SEOs and website owners should know.

Common Argument About Robots.txt

Seems like any time the topic of Robots.txt comes up there’s always that one person who has to point out that it can’t block all crawlers.

Gary agreed with that point:

“robots.txt can’t prevent unauthorized access to content”, a common argument popping up in discussions about robots.txt nowadays; yes, I paraphrased. This claim is true, however I don’t think anyone familiar with robots.txt has claimed otherwise.”

Next he took a deep dive on deconstructing what blocking crawlers really means. He framed the process of blocking crawlers as choosing a solution that inherently controls or cedes control to a website. He framed it as a request for access (browser or crawler) and the server responding in multiple ways.

He listed examples of control:

• A robots.txt (leaves it up to the crawler to decide whether or not to crawl).
• Firewalls (WAF aka web application firewall – firewall controls access)
• Password protection

Here are his remarks:

“If you need access authorization, you need something that authenticates the requestor and then controls access. Firewalls may do the authentication based on IP, your web server based on credentials handed to HTTP Auth or a certificate to its SSL/TLS client, or your CMS based on a username and a password, and then a 1P cookie.

There’s always some piece of information that the requestor passes to a network component that will allow that component to identify the requestor and control its access to a resource. robots.txt, or any other file hosting directives for that matter, hands the decision of accessing a resource to the requestor which may not be what you want. These files are more like those annoying lane control stanchions at airports that everyone wants to just barge through, but they don’t.

There’s a place for stanchions, but there’s also a place for blast doors and irises over your Stargate.

TL;DR: don’t think of robots.txt (or other files hosting directives) as a form of access authorization, use the proper tools for that for there are plenty.”

Use The Proper Tools To Control Bots

There are many ways to block scrapers, hacker bots, search crawlers, visits from AI user agents and search crawlers. Aside from blocking search crawlers, a firewall of some type is a good solution because they can block by behavior (like crawl rate), IP address, user agent, and country, among many other ways. Typical solutions can be at the server level with something like Fail2Ban, cloud based like Cloudflare WAF, or as a WordPress security plugin like Wordfence.

Read Gary Illyes post on LinkedIn:

robots.txt can’t prevent unauthorized access to content

Featured Image by Shutterstock/Ollyy

Google Clarifies Autocomplete Functionality Amid User Concerns via @sejournal, @MattGSouthern

Google’s Communications team recently took to X to clarify its Search Autocomplete feature following user complaints and misconceptions.

Autocomplete’s Purpose & Functionality

Addressing claims of search term censorship Google stated:

“Autocomplete is just a tool to help you complete a search quickly.”

Google notes that users can always search for their intended queries regardless of Autocomplete predictions.

Recent Issues Explained

Google acknowledged two specific problems that had sparked user concerns.

Addressing lack of predictions for certain political queries, Google says:

“Autocomplete wasn’t providing predictions for queries about the assassination attempt against former President Trump.”

Google claims this was due to”built-in protections related to political violence” that were outdated.

The company said it’s working on improvements that are “already rolling out.”

Google also addressed missing autocomplete predictions for some political figures.

Google described this as:

“… a bug that spanned the political spectrum, also affecting queries for several past presidents, such as former President Obama.”

The issue extended to other queries like “vice president k,” which showed no predictions.

Google confirmed it’s “made an update that has improved these predictions across the board.”

Algorithmic Nature Of Predictions

Google emphasized the algorithmic basis of its prediction and labeling systems, stating:

“While our systems work very well most of the time, you can find predictions that may be unexpected or imperfect, and bugs will occur,”

The company noted that such issues are not unique to their platform, stating:

“Many platforms, including the one we’re posting on now, will show strange or incomplete predictions at various times.”

Commitment To Improvement

The thread concluded with a pledge from Google to address issues as they arise:

“For our part, when issues come up, we will make improvements so you can find what you’re looking for, quickly and easily.”

Broader Context

This explanation from Google comes at a time when tech companies face increasing scrutiny over their influence on information access.

This incident also highlights the broader debate about algorithmic transparency in tech.

While autocomplete might seem like a background feature, it significantly impacts what people search for and the websites they visit.

Featured Image: Galeh Nur Wihantara/Shutterstock