SEOs Are Recommending Structured Data For AI Search… Why? via @sejournal, @martinibuster

A post on LinkedIn questioned the idea that Schema.org structured data has an impact on what a large language model outputs. Apparently there are some SEOs who are recommending structured data to rank better in AI search engines.

Patrick Stox wrote the following post on LinkedIn:

“Did I miss something? Why do SEOs think schema markup will impact LLM output?”

Patrick said “LLM output” in the context of an SEO recommendation so it’s likely that it’s a reference to ChatGPT Search and other AI search engines. So do AI search engines get their data from structured data?

LLMs are trained on web text, books, government records, legal documents and other text data (as well as other forms of media, too) which is then used to produce summaries and answers but without plagiarizing the training data.  What that means is that it’s pointless to think that optimizing your web content will result in the LLM itself sending referrals to that website.

AI search engines are grounded on search indexes (and knowledge graphs) through Retrieval Augmented Generation (RAG). Search engine indexes themselves are created from crawled data, not Schema structured data.

Perplexity AI ranks web-crawled content using a modified version of PageRank on their search index, for example. Google and Bing crawl text data and do things like remove duplicate content, remove stop words, and other manipulation of the text extracted from the HTML, plus not every page has structured data on it.

In fact, Google only uses a fraction of the available Schema.org structured data for specific kinds of search experiences and rich results, which in turn limits the kind of structured data that publishers use.

Then there’s the fact that both Bing and Google’s crawlers render the HTML, identify the headers, footers and main content (from which they extract the text for ranking purposes). Why would they do that if they’re going to rely on Schema structured data, right?

The idea that it’s good to use Schema.org structured data to rank better in an AI search engine is not based on facts, it’s just fanciful speculation. Or it could be from a “game of telephone” effect where one person says something and then twenty people later it’s transformed into something completely different.

For example, Jono Alderson proposed that structured data could be a standard that AI search engines could use to understand the web better. He wasn’t saying that AI search engines currently use it, he was just proposing that AI search engines should consider adopting it and maybe that post got telephoned into a full-blown theory twenty SEOs later.

Unfortunately, there’s a lot of unfounded ideas floating around in SEO circles. The other day I saw an SEO assert in social media that Google Local Search doesn’t use IP addresses in response to search “near me” search queries. All anyone had to do to test that idea is to sign into a VPN, choose a geographic location for their IP address and do a “near me” search query and they will see that the IP address used by the VPN influenced the “near me” search results.

Screenshot Of Near Me Query Influenced By IP Address

Google even publishes a support page that says they use IP address to personalize search results yet there are people who believe otherwise because some SEO did a correlation study and when questioned we’re back to someone bellowing that Google lies.

Will You Believe Your Lying Eyes?

Schema.Org Structured Data And AI Search Results

“SEOs” recommending that publishers use Schema.org structured data for LLM training data also makes no sense because training data isn’t cited in LLM output, just for output that is sourced from the web, which itself is sourced from a search index that’s from a crawler. As mentioned earlier, publishers only use a fraction of available Schema.org structured data because Google itself only uses a tiny fraction of it. So it makes no sense for an AI search engine to rely on structured data for their output.

Search marketing expert Christopher Shin (LinkedIn profile) commented:

“Thinking the same thing after reading your post Patrick. This is how I interpret it currently. I thought LLM’s typically do not generate responses from search engines serps but rather from data interpretation. Right? But schema data markup would be used by SER{s to show rich snippets etc. no? I think the key nuance with schema and LLMs is that search engines use schema for SERPs whereas LLM’s use data interpretation when it comes to how schema impacts LLM’s.”

People like Christopher Shin and Patrick Stox give me hope that pragmatic and sensible SEO is still fighting to get through the noise, Patrick’s LinkedIn post is proof of that.

Pragmatic SEO

The definition of pragmatic is doing things for sensible and realistic reasons and not on opinions that are based on incomplete information and conjecture.

Speaking as someone who’s been involved with SEO since virtually the birth of it, not thinking things through is why SEOs and publishers have traditionally wasted time with vaguely defined issues, spun their wheels on useless activities like superficial signals of EEAT and so on and so forth.  It’s truly dispiriting to point to documentation and official statements and get blown back with statements like, “Google lies.” That kind of attitude makes a person “want to holler.”

A little more pragmatic SEO please.

What Happens Next To The U.S. Vs. Google Antitrust Case? via @sejournal, @AlliBerry3

With the punishment for Google’s first search antitrust case expected to be delivered in August 2025, the looming question is what will happen now with a new U.S. President and a new set of Department of Justice (DOJ) appointees.

Early signs suggest the Trump administration will largely stay the course of the Biden administration when it comes to antitrust enforcement against large tech companies, including Google.

Their rationale is drastically different from that of the previous administration, but the recent nominations and appointments for the DOJ suggest that President Trump is serious about holding Google accountable, even if their preferred remedies may differ.

Before we get into it, let’s recap what has happened so far.

The U.S. Vs. Google Case

In August 2024, Federal Judge Amit Mehta ruled that Google violated the U.S. antitrust law by maintaining an illegal monopoly through exclusive agreements it had with companies like Apple to be the world’s default search engine on smartphones and web browsers.

Additionally, Google was found guilty of monopolizing general search text advertising because Google was able to raise prices on search advertising products higher than what the government claimed would have been expected or possible in a fair market.

Potential Remedies For Google

The DOJ submitted two filings with their suggestions to remediate Google’s monopolistic actions.

Proposed remedies range from restrictions on deals that feature Google’s search engine as the default on browsers and devices all the way to a breakup of the company by forcing the sale of Google’s browser Chrome.

Other intriguing remedies that have been proposed include syndicating the Google search algorithm to competitors, forced licensing of ad feeds to competitors, and divesting the Android operating system.

The DOJ under Biden made it clear in their most recent filing on November 20, 2024, that divesting Chrome is their preferred option, along with the discontinuation of exclusive agreements with browsers and phone companies.

The implications of divesting Chrome are also the most wide-reaching – not only is Chrome used by nearly two-thirds of the world’s internet users, but we learned through this trial that click data from Chrome is used to train the search algorithms using Navboost, helping Google maintain its competitive edge.

Losing Chrome’s data would almost certainly guarantee a drastically different Google search engine.

Google filed its response to the DOJ, arguing that the proposed remedies are much wider reaching than what the case was about and that America’s global leadership position in tech could be hindered by this.

Instead, they proposed allowing exclusive agreements to be made with companies like Apple and Mozilla, but with the ability to set a different default search engine on different platforms and browsing modes.

It also proposed that Android device manufacturers could preload multiple search engines, as well as preload Google apps without Google Search or Chrome.

Both sides will return to court for the remedies litigation in May 2025, with a ruling expected to be delivered in August 2025.

What Happens Now

Back to the question at hand: What happens once Trump takes office?

The initial signals, including Trump’s nominations for key roles at the FTC and the Department of Justice Antitrust Division, suggest the administration will continue to use a heavy hand against large tech companies facing antitrust troubles like Google. But, their solutions may differ from the current proposed remedies.

Trump’s Relevant Nominees

Trump has nominated several key individuals who will influence antitrust enforcement, particularly concerning Big Tech companies.

These appointments indicate that the crackdown on tech giants will likely continue, in effect, a surprising bipartisan effort. Trump’s key nominees include:

• Gail Slater: Nominated to lead the Department of Justice’s Antitrust Division, Slater has a background as a policy advisor to Vice President-elect J.D. Vance and experience in tech policy at the National Economic Council. If confirmed, she would inherit the antitrust case against Google.
• Andrew N. Ferguson: Appointed as Chair of the Federal Trade Commission (FTC), Ferguson has expressed intentions to reassess the agency’s approach to mergers and acquisitions, which has been uncommonly strong against mergers and acquisitions, while still maintaining oversight of dominant tech platforms.
• Mark Meador: Appointed as an FTC Commissioner, a role previously held by Ferguson, Meador is recognized for his pro-enforcement stance, especially regarding technology companies, in his previous work with the U.S. Senate Judiciary Committee. His previous work includes drafting legislation aimed at addressing competitive practices in the tech industry.

While all three of these nominees are deeply rooted in the Republican party, they are all united in their pro-enforcement stances when it comes to Big Tech.

This is a departure from the typical Republican pro-business, anti-regulation position, signifying Trump’s seriousness in curbing the power of Google and other tech giants.

The Trump Administration’s Views On Google’s Antitrust Case

Trump’s disdain for Big Tech companies, including Google, has been consistent since his first presidency.

Why does he hate Google so much? A couple of reasons seem most likely:

1. He has claimed the search engine is “rigged” because it presents negative stories about him.
2. He sees weakening Big Tech companies as a way to promote “free speech” because of their misinformation moderation policies and claims the search results are biased against conservatives.

Despite this seemingly constant position against Google, President Trump has also suggested that breaking Google up may destroy the company rather than help promote fairness and competition.

He has also warned that breaking up Google may make the U.S. appear weaker to foreign powers because “China is afraid of Google.”

Elsewhere in the administration, Vice President Vance has previously called for the breakup of Google and praised the Biden administration’s Federal Trade Commission Chair, Lina Khan, for her aggressive approach to antitrust enforcement.

Whether they decide to take a stance that is pro-breaking Google up remains to be seen, but it appears that they will be taking office with a desire to strengthen competition in this market.

Final Thoughts

There is a lot of time between Trump taking office and the remedies litigation starting up again for the case against Google in May 2025.

The DOJ still needs to argue why they believe Google should be forced to sell Chrome, and if this is no longer the belief of the DOJ appointees, they will need to argue why other remedies make more sense.

It seems reasonable to assume, based on the appointees, that they will be taking some big swings at Google and arguing for the remedies that they believe would be most effective at enhancing competition.

If you are someone who believes action needs to be taken against Google, Trump’s current anti-Google stance may work in your favor regardless of whether you agree with his rationale for it.

More Resources:

Featured Image: PanuShot/Shutterstock

Google Updates Site Reputation Abuse Policy Documentation via @sejournal, @MattGSouthern

Google has updated its documentation to provide clearer guidance on its site reputation abuse policy.

The changes are meant to you better understand what qualifies as a violation and how to stay compliant.

While the updates don’t change how the policy is applied, they make the rules easier to follow by incorporating more detailed explanations from a recent blog post FAQ.

What Changed?

The updated documentation now includes content directly pulled from Google’s November blog post about site reputation abuse.

That blog post introduced a Q&A section to clarify the policy. Google has now added this FAQ guidance to its official spam policies documentation.

In a statement, Google explained:

“We updated the site reputation abuse policy to include guidance from our blog post’s FAQ on site reputation abuse. These are editorial changes only, no change in behavior.”

This means the policy hasn’t changed—it’s just been rewritten to make it easier to understand.

What Is Site Reputation Abuse?

Site reputation abuse happens when third-party content is published on a well-established website to take advantage of that site’s ranking signals.

Essentially, it occurs when someone uses a reputable site as a shortcut to boost rankings for unrelated or low-quality content rather than earning those rankings independently.

For example:

• A news site hosting coupon pages from a third-party service purely to benefit from the site’s strong rankings in Google.
• An educational site publishing sponsored reviews about payday loans.
• A movie review site hosting unrelated pages about essay writing services or buying social media followers.

However, not all third-party content is considered abuse. Forums, user-generated content, syndicated news articles, and editorial pieces are generally acceptable if they’re not designed to manipulate search rankings.

Why Does This Matter?

These updates make it easier to determine whether your content violates the policy.

For example, Google’s FAQ now clarifies common scenarios, such as:

• Third-party content: Simply having third-party content isn’t a violation unless explicitly published to exploit a site’s rankings.
• Freelance and affiliate content: Freelance content or affiliate pages are acceptable if they’re not used to manipulate rankings. Affiliate links, when tagged appropriately (e.g., with “nofollow” or “sponsored” attributes), don’t violate the rules.

The FAQ also explains how to address violations. You can fix the issue by removing or relocating problematic content, submitting reconsideration requests in Search Console, and following Google’s spam guidelines.

This is a good reminder to review your content practices to ensure they align with Google’s policies. If you host third-party content, make sure it adds value for users and doesn’t just serve to piggyback off your site’s reputation.

Featured Image: RYO Alexandre/Shutterstock

Google’s Documentation Update Contains Hidden SEO Insights via @sejournal, @martinibuster

Google quietly updated their Estimated Salary (Occupation) Structured Data page with subtle edits that make the information more relevant and easily understood. The changes show how a page can be analyzed for weaknesses and subsequently improved.

Subtle Word Shifts Make A Difference

The art of writing is something SEO should consider now more than ever. It’s been important for at least the past six years but in my opinion it’s never been more important than it is today because of the preciseness of natural language queries for AI Overviews and AI assistants.

Three Takeaways About Content

1. The words used on a page can exert a subtle influence in how a reader and a machine understand the page.
2. Relevance is commonly understood as whether a web page is a match for a user’s search query and the user’s intent, which is an outdated way to think about it, in my opinion.
3. A query is just a question and the answer is never a web page. The answer is generally a passage in a web page.

Google’s update to their “Estimated Salary (Occupation) Structured Data” web page offers a view of how Google updated one of their own web pages to be more precise.

There were only two changes that were so seemingly minimal they didn’t even merit a mention on their documentation changelog, they just updated it and pushed it live without any notice.

But the changes do make a difference in how precise the page is on the topic.

First Change: Focus Of Content

Google refers to “enriched search results” as different search experiences, like the recipe search experience, event search experience and the job experience.

The original version of the “Estimated Salary (Occupation) Structured Data” documentation focused on talking about the Job Experience search results. The updated version completely removed all references to the Job Experience and is now more precisely focused on the “estimated salary rich result” which is more precise than the less precise “Job Experience” phrasing.

This is the original version:

“Estimated salaries can appear in the job experience on Google Search and as a salary estimate rich result for a given occupation.”

This is the updated version:

“Adding Occupation structured data makes your content eligible to appear in the estimated salary rich result in Google Search results:”

Second Change: Refreshed Image And Simplified

The second change refreshes an example image.

The change has three notable qualities:

1. Precisely models a search result
2. Aligns with removal of “job experience”
3. Simplifies message

The original image contained a screenshot of a laptop with a search result and a closeup of the search result overlaid. The image looks more at home on a product page than an informational page. Someone spent a lot of time creating an attractive image but it’s too complex and neglects the number one rule of content which is that all content must communicate the message quickly.

All content, whether text or image, is like a glass of water: the important part is the water, not the glass.

Screenshot Of Attractive But Slightly Less Effective Image

The image that replaced it is literally an example of the actual rich result. It’s not fancy but it doesn’t have to be. It just has to do the job of communicating.

Screenshot Of Google’s More Effective Image

The other thing this change accomplishes is that it removes the phrase “job experience” and replaces it with a sentence that aligns with the apparent goal of making this page about the Occupation structured data.

This is the new text:

“Adding Occupation structured data makes your content eligible to appear in the estimated salary rich result in Google Search results:”

Third change: Replace Confusing Sentence

The third change corrected a sentence that was grammatically incorrect and confusing.

Original version:

“You must include the required properties for your content to be eligible for display the job experience on Google and rich results.”

Google corrected the grammar error, made the sentence specific to the ‘estimated salary’ rich result, and removed the reference to Job Experience, aligning it more strongly with estimated salary rich results.

This is the updated version:

“You must include the required properties for your content to be eligible for display in the estimated salary rich result.”

Three Examples For Updating Web Pages

On one level the changes were literally about removing the focus on one topic and reinforcing a slightly different one. On another level it’s an example of giving users a better experience by communicating more precisely. Writing for humans is not just a creative art, it’s also a technical one. All writers, even novelists, understand that the craft of writing is technical because one of the most important factors is communicating ideas. Other issues like being comprehensive or fancy don’t matter as much as the communication part.

I think that the revisions Google made fits into what Google means when it says to make content for humans not search engines.

Read the updated documentation here:

Estimated salary (Occupation) structured data

Compare it to the archived original version.

Featured Image by Shutterstock/Lets Design Studio

Confirmed: Google Is Requiring JavaScript To Block SEO Tools via @sejournal, @martinibuster

Google has made a change to how it’s search results are served which will also help to secure it against bots and scrapers. Whether this will have further effect on SEO Tools or if they can use a headless Chrome that uses JavaScript remains an open question at the moment but it’s likely that Google is using rate limiting to throttle how many pages can be requested within a set period of time.

Google Search Now Requires JavaScript

Google quietly updated their search box to require all users, including bots, to have JavaScript turned on when searching.

Surfing Google Search without JavaScript turned on results in the following message:

Turn on JavaScript to keep searching
The browser you’re using has JavaScript turned off. To continue your search, turn it on.

Screenshot Of Google Search JavaScript Message

In an email to TechCrunch a Google spokesperson shared the following details:

“Enabling JavaScript allows us to better protect our services and users from bots and evolving forms of abuse and spam, …and to provide the most relevant and up-to-date information.”

JavaScript possibly enables personalization in the search experience, which is what that spokesperson may mean by providing the most relevant information. But JavaScript can also be used for blocking bots.

Using the latest version of Chrome I copied some of the JavaScript and ran it through ChatGPT to ask what it does. One part of it may relate to restricting abusive requests for documents.

Screenshot Of Chrome Dev Tools

ChatGPT gave me the following feedback:

“Core Functionalities
Randomized Value Generation (rdb)

Generates a random value based on properties (D_d, idc, and p4b) of the input object a, constrained by p7d.
This may be used for rate-limiting, exponential backoff, or similar logic.

Purpose and Context
From its components, the script:

Likely handles request retries or access control for web resources.

Implements a policy enforcement system, where:

Policies determine if requests are valid.

Errors are logged and sometimes retried based on rules.

Randomized delays or limits might control the retry mechanism.

Appears optimized for error handling and resilience in distributed or high-traffic systems, possibly within a Google service or API.”

ChatGPT said that the code may use rate-limiting which is a way to limit the number of actions a user or a system can take within a specific time period.

Rate-Limiting:

Used to enforce a limit on the number of actions (e.g., API requests) a user or system can perform within a specific time frame.
In this code, the random values generated by rdb could be used to introduce variability in when or how often requests are allowed, helping to manage traffic effectively.

Exponential Backoff:

ChatGPT explained that exponential backoff is a way to limit the amount of retries for a failed action a user or system is allowed to make. The time period between retries for a failed action increases exponentially.

Similar Logic:

ChatGPT explained that random value generation could be used to manage access to resources to prevent abusive requests.

I don’t know for certain that this is what that specific JavaScript is doing, that’s what ChatGPT explained and it definitely matches the information that Google shared that they are using JavaScript as part of their strategy for blocking bots.