Google is WRONG: structured data does impact your site’s ranking.

Google wrote that “structured data won’t make your site rank better”. Many SEOs seriously believe this. I respect their opinion but my supposed understanding of Google Search’s mechanism is entirely different and it is based on real-world data.

In my opinion, those who believe this statement:

1) Misunderstand how Google Search works

2) Do not think critically (sorry, it is a lost art)

Do I believe the official Google Search statement you just read is misleading? Absolutely! A good structured data strategy will positively impact organic rankings. I’ll do my best to explain things in detail.

My core argument is simple: structured data → CTR → rankings. Do I believe there’s a lot more regarding semantic search? Yes! Will some argue that I’m just sharing theories? Yes! Do I wish them the best? Yes! 🙂

In theory, I’d have two ways of explaining things:

• The easy way: if you saw the statistically significant real-world data I collected, any argument would instantly stop at this stage because you’d be convinced. But this isn’t an option because I’ll never reveal details covered by NDAs. Just know we’re talking of case studies for the 2024-2025 period: all extremely recent.
• The exciting way: I find explaining the underlying logic more challenging because I don’t want people to trust me (or my data). Do NOT blindly believe Google. And don’t blindly believe me either. Think for yourself.

Any senior enterprise SEO consultant in charge of ranking millions of pages knows that websites with high-quality structured data get richer results, leading to better CTR and rankings.

However, the funny thing is that while even senior SEOs might know this intuitively after seeing the real-world results, they might not always be able to explain exactly why what they see is happening.

In this article, I’ll do my best to explain the WHY and the HOW, step by step.

Some will argue that this is just my personal and subjective opinion. And since I won’t share confidential case studies, they might seem right. Just know my “subjective” opinion is based on real-world results. When you’ve seen what I’ve seen, all the public statements and drama mean nothing.

DISCLAIMER 1: I do not pretend to have any kind of privileged access to Google’s internal systems but the reasoning and deductions I’ll push you to make while reading will be straightforward enough to reach the obvious conclusion. If you don’t believe me at the end, no problem.

DISCLAIMER 2: I don’t have any personal vendetta against anyone. I actually appreciate many people at Google, but the company has been going in the wrong direction. Many statements have turned out to be false over the years. I believe debunking false statements is an obligation. This is risky for me but I’m not counting on the support of anyone.

Because not everyone has the same level of technical sophistication, I will remind the readers of a few basic concepts.

Structured data in search

Structured data in the context of organic search is simply an additional layer of information specifically aimed at search engines that adds context and maps the relationships between entities (but this can also influence AI engines).

We have the visible and relatively “unstructured” content served to human visitors on the web pages and we have the invisible but structured content for the robots. That last part is what we call “structured data”.

To “speak” to robots, we use a specific vocabulary (like Schema), and we rely on different encodings, including RDFa, Microdata and JSON-LD, to define entities such as products, events, people or companies and their relationships.

Structured and unstructured data: optional vs required

The UNSTRUCTURED CONTENT that’s visible to humans is REQUIRED.

The STRUCTURED DATA that’s only visible to robots is OPTIONAL.

The question is: how powerful is this optional data?
The answer is: beyond anything you can imagine.

Remember: the visible content is the foundation on which everything is built.

How structured data adds value for humans

When SEO “experts” focus on machine interpretability, they consider only the code but completely overlook the visual enhancement that directly benefits human perception. Structured data enhances the user experience by making search results more beautiful, clearer and less cognitively demanding.

The wealth of information presented directly in rich results reduces the cognitive effort humans require.

The content’s intrinsic quality remains unchanged but because its visibility and usability improve, this indirectly boosts its impact. That point alone is critical. Structured data itself doesn’t inherently change the quality of the underlying content but the improved presentation of that content through rich results will influence a user’s perception of its relevance.

Most people seem unaware that structured data can enhance accessibility and perceived value. To put it simply, structured data makes high-quality content stand out and easier to find!

What structured data can do: real-world examples

Structured data enables search engines to display rich results, which stand out compared to plain text listings. For example:

• A recipe page might show a photo of the dish, a star rating, and cooking time right in the SERP.
• A product listing could include pricing, availability and reviews.
• An event might feature dates and locations upfront.

These elements make the search results “beautiful”: they break the monotony of text listings with visual cues. This aesthetic improvement isn’t superficial: it draws our human attention, increases engagement, and makes the experience more enjoyable. As you can see, structured data is far from being a machine-only feature. It adds a visual appeal that directly benefits humans by transforming a wall of text into something more inviting and more intuitive.

Case studies: structured data impacts CTR & session quality

SEOs might disagree with my underlying logic. They are more than welcome to share their counterarguments but regarding the impact of structured data on CTR and session quality, it is time to remind everyone of a few public case studies.

• Rotten Tomatoes added structured data to 100,000 unique pages and measured a 25% higher click-through rate for pages enhanced with structured data, compared to pages without structured data.
• The Food Network has converted 80% of their pages to enable search features, and has seen a 35% increase in visits.
• Rakuten has found that users spend 1.5x more time on pages that implemented structured data than on non-structured data pages, and have a 3.6x higher interaction rate on AMP pages with search features vs non-feature AMP pages.
• Nestlé has measured pages that show as rich results in search have an 82% higher click through rate than non-rich result pages.

Source? Google itself! Structured data impacts CTR and qualified traffic 😀

Structured data and matching search intentions

People in Search often ignore how structured data helps search engines to better understand user intent (what a user is looking for) and search intent (the type of content that best matches a search query). The final goal should be to serve results matching the user’s intentions.

The question is: how can structured data that does NOT trigger rich results be beneficial?

It is simple: there’s an indirect and invisible benefit of structured data regarding semantic search because it makes it easier for Google to serve a result with the exact “entity” the user was searching for without them having to remember the name of the brand, product, service, person, website, etc…

Let me explain: structured data adds context to the content and interconnects external entities.

To oversimplify, when the data is clean and accurate, an internal knowledge graph stored on Google’s end progressively grows. And then machine learning systems are in charge of understanding the users’ hidden search intentions and matching them with the best possible content.

That’s how structured data can help with semantic search. There are two different systems interacting with each other. In other words, even WITHOUT the visual benefit of rich results, structured data can add a layer of contextual understanding for search engines that will help match the search intent!

A made up semantic search example

Modern search engines rely on semantic understanding: they understands the meaning of the data, not just the keywords. And structured data plays an essential role in this. To illustrate, I will create a virtual organic shampoo named NoobShine and costing $19.98. My shampoo will be manufactured by the brand GreenBrand and sold by a e-commerce website named GreenProducts. And the creator will be me: Elie Berreby.

Imagine someone saw a fantastic review for my GreenShamp product but forgot the name and they simply search for “organic cruelty-free shampoo under $20” structured data with the additionalCharacteristics (organic, cruelty-free) and offers (price) makes it much easier for the engine to identify the product as a perfect match, even if the exact names GreenShamp, GreenBrand or GreenProducts aren’t present the search query.

If I use @id properties for Product, Brand, Offer, Review, I’ll add support for linked data principles, which allows entities to be uniquely identified and potentially referenced across datasets! The @id property is used to assign a unique identifier (typically a URI or IRI) to an entity. And this identifier goes beyond the local scope of the HTML document. Once your entities have stable @ids, other datasets or systems can reliably refer to them which makes the strategy very powerful!

My final structured data code will play a role in cross-entity understanding: the search engine can understand that Elie Berreby at GreenBrand Labs Inc. developed the NoobShine Shampoo for GreenBrand, sold on GreenProducts. This network of understanding will allow the engine to serve results based on search queries related to the creator, manufacturer or specific characteristics linked through these relationships, which would be impossible with just unstructured text.

Good structured data is essential in semantic search because it makes it easier for Google to serve the exact product the user was searching for without them having to remember the name of the brand, product or website. But at least two systems within Google have to communicate: the internal knowledge graph (made up of unstructured content + structured data) and the machine learning solution in charge of understanding the user intent. And there’s actually a third system at play 🙂

The data war is escalating

We live in a new era of data acquisition. Search engines now find themselves in direct competition with aggressive AI crawlers that are engineered for rapid and extensive web scraping. There’s an intense struggle for data dominance. We have the good bots obeying the “Robots Exclusion Protocol” and the bad bots whose only law is the data they find and extract.

Amid this data war, search engines themselves might become more aggressive as they evolve into hybrids combining traditional organic search and generative AI models tailored for Search.

That can only mean one thing for the future of Search: good structured data will soon be used not just by search engines but by most conversational AI models desperately attempting to reduce computational costs.

We live in the generative AI era in which anything that provides information gain will be scraped. With structured data, we can send an invisible but very rich layer of information to “speak” directly to “machines”. 

High-value structured data requiring less computational resources isn’t ignored. I hope we will at least agree on this: it isn’t in the search engine’s interest (or anyone for that matter) to ignore structured data… Except in the following two cases.

Why is Google Downplaying the Power of Structured Data for SEO?

Good structured data is correlated to content: it should be embedded within the HTML of the page and used to describe the content that’s already there and the relationships with what might not be there (cross-referencing). With structured data, there’s the content description, the context and the relationships. But there are two types of BAD structured data:

1. Poorly written: that will obviously fail but there’s no malicious intent.

2. Perfectly written… but intentionally misleading (when people cheat).

Cheaters use structured data to send false signals: what they describe does not exist in reality. Cheaters pollute the internet with noisy and inaccurate data. To be useful, structured data must be clean and without error.

Google has some ability to detect structured data that does not add value. The system isn’t perfect but it exists.

When honest people implement qualitative Schema markup, they aim to enhance their legitimate search engine results by getting rich “snippets”. Rich results aren’t systematic but there’s a higher probability of getting them if the code adds value instead of noise.

Click-Through Rates & Rankings

Before I explain why these visually appealing snippets are proven to improve click-through rates (CTR), remember that leaked Google algorithm API documentation suggests that CTR is a ranking signal. It is more than a suggestion: years before the so-called “leak”, the impact of CTR was an open secret within black-hat SEO circles, with many groups taking advantage of this knowledge and manipulating Click-Through Rates to generate millions.

After I began warning Google in 2023, John Mueller first thanked me, and suggested an in-person discussion but…

…but apparently I ended up blocked shortly after. I was just trying to help but I understand this might have seemed scary. No hard feelings: I didn’t read official statements before, and I’m not reading them today.

I only realized I was blocked about a year later when my followers asked me questions with links I couldn’t access. It seems I’m blocked on Mastodon, Linkedin, etc. Understandable: I’d probably block myself as well if I could! 😀

But in all seriousness, CTR manipulation is why I suspect we had what I consider to be a deeply misleading statement by Google in April 2025. I believe Google might want to avoid bad actors manipulating SERPs. Some SEOs will strongly disagree with me and defend the official Google statements. That’s okay. Everyone is entitled to their opinion. But what if facts contradict opinions?

Cheaters abused Google through many other SERP manipulation tactics in the past. And Google likely wants to avoid seeing this again. The intention might be “good” but misleading individuals and companies isn’t the way.

With structured data, the abuse would be less direct but everything remains incredibly simple:

• Well-written structured data leading to richer results,
• Higher CTR because the results are more appealing,
• Positive divergence between the estimated CTR on Google’s end and the real-world CTR,
• Google is pushed to automatically attribute better rankings to the sites/pages with the high CTR.

If I’m wrong and Google isn’t actually trying to mislead readers to avoid cheating and abuse, then I’m sorry but some Google’s spokespersons might seriously lack understanding of the basic search concepts I’ll expose now…

Layout influences human behavior

Screen real estate is precious because it is extremely limited, and everyone competes for the top ranks. SEO is a zero-sum game: when you rank first, someone else has to de-rank. In SEO, your wins are somebody else’s losses.

Layout influences behavior simply because how things are designed impact human-machine interactions. This is a fundamental principle in fields like Human-Computer Interaction (HCI), User Experience (UX) design and even psychology.

Rich results incorporate visual elements like images, videos, star ratings, event dates, product prices, and more. These elements are visually more appealing than basic text snippets. And our eyes are naturally drawn to visual stimuli, which makes those rich results stand out: they receive more attention.

Clarity & Reduced Cognitive Load

Instead of users having to click through to a website to find specific information (like a product price, review score, or event date), rich results often display this information directly in the SERPs. And paradoxically, because this reduces the cognitive load required to evaluate the relevance of a result, users usually decide to click more. And qualified traffic increases.

Rich results allow humans to make more informed “clicking decisions”. As humans, we are more likely to click on a result that provides relevant details upfront, leading to higher quality traffic for the website. Even a superficial understanding of human psychology explains why structured data, by making search results more “beautiful” slightly impacts the layout of SERPs. And the tiniest layout improvement will influence the user behavioral patterns, including where they click and how often they click!

CTR divergences & Google’s machine learning predictions

Many do not realize this but Google uses predictive analytics models to determine the expected click-through rate. And whenever there’s a divergence between their predictive analytics models and the real-world results, Google automatically re-evaluates organic rankings. Positively or negatively.

How does Google track the historical performance of URLs? Simple! Google analyzes the CTR of various URLs for specific search queries. This includes data on how often users clicked on a particular result when it appeared for a given query. Using machine learning, Google identifies patterns in which titles, snippets and positions tend to receive more clicks.

For example, if an AI overview is above a traditional organic result, Google knows the CTR of the subsequent organic results will be significantly lower. Everyone in SEO is empirically aware of the damage. But Google sees the precise numbers and that’s why data related to AI overviews isn’t shared in Google Search Console at this stage. It would be highly problematic.

Ahrefs recently analyzed 300k keywords and estimated that the presence of an AI Overview in the search results correlated with a 34.5% lower average Click-Through Rate (CTR) for the top-ranking page compared to similar informational keywords without an AI Overview… Almost all the case studies senior profiles shared with me suggest that AI overviews lead to a CTR decline between 30 and 40%. Some were outliers with percentages outside of this range.

But Google also uses aggregated and anonymized user behavior data (beyond just clicks) to refine its predictions. This includes dwell time on a page after clicking, users quickly returning to the SERPs (not happy with the page), and other engagement metrics. Machine learning helps to correlate these behaviors with the initial click and predict future CTR.

When the real-world CTR differs significantly from expected results, Google’s carefully crafted CTR predictions are off and this triggers an internal re-evaluation: Google Search must reconsider. This is perceived as an anomaly.

You already knew that ranks were a strong predictor of CTR: higher ranks get more clicks… But machine learning models go way beyond this type of simple correlation. They learn that the expected CTR for a specific position varies depending on the search query, the type of content and the presence of SERP features… Hello, structured data my old friend! 🙂

You see, anything that can enhance a result and make it “richer” will likely lead to higher conversion rates. If I manage to get a visually more appealing organic result, this attracts attention and clicks. And any unusually high real-world CTR will create a positive divergence between Google’s expected CTR.

CTR impacts rankings

When human users love a website, they click on it. Google immediately notices this positive indirect signal. If the trend is confirmed, Google reconsiders the rankings because something, somewhere is deeply satisfying for humans. That’s quality and as a search engine, that’s what you want to rank at the top!

Some will argue that CTR isn’t a direct ranking factor. Direct or indirect? Ranking factor or ranking signal? What matters is having a good understanding of both organic search and human behavior.

I really couldn’t care less what is or isn’t officially a ranking factor. I care about real-world results.

And here’s an example of how things work in practice (this is something I never published until now).

The relative weight of a low rank getting interest signals to Google a weight swift because it signifies to the search engine that the user interest is higher for the lowered ranked result.

— Elie Berreby

In other words, what I just wrote means that a high CTR, let’s imagine 4.2%, on a website ranked in position 7 is more important and meaningful for Google, than the exact same CTR of 4.2% on a site ranked in position 1 or 2.

How structured data improves your website ranking

Structured data makes your content eligible for rich results.

• Because rich results are visually enhanced, they stand out in the SERPs.
• Because rich results stand out, they attract more human attention and increase the likelihood of clicks. Improved layout and clearer information directly presented in the SERPs significantly influence user behavior and the CTR increases.
• Higher CTR indirectly signals to Google that your result is relevant and valuable for the search query.
• Google considers the indirect ranking signal (higher CTR) and your site ranks “better” over time.

Elie Berreby’s final remarks about structured data

Structured data provides search engines with explicit clues about the meaning and context of your content. Instead of relying solely on their algorithms to interpret content, Google can understand precisely what your page is about thanks to the additional layer of information good structured data provides.

This improved understanding increases the probability of your content being shown for relevant search queries. And when search engines understand your content better, they can more accurately match it to user search intent. Beyond CTR as an indirect ranking signal, that’s another reason your pages will rank higher for the right keywords. And you’ll attract a more qualified audience.

Structured data helps search engines understand and present information. Because it also helps humans cognitively, the use of structured data is likely to grow, especially with the rise of AI and semantic search.

Websites that provide accurate and clear structured data are better positioned to benefit from future algorithm updates.

I’d love it if Google decided to apply severe penalties to those who cheat and abuse structured data to signal things that don’t exist. Instead of misleading readers and telling them that structured data does not help websites rank better, Google should penalize the cheaters.

— Elie Berreby

Content theft, engagement theft, and multichannel organic strategies

As Google transitions from a search engine to an AI giant, the SERPs in Google keep decreasing in quality. The search engine became a “hybrid” and scraped high-value content created by humans. This content used to be what creators and publishers relied on to differentiate themselves and attract organic leads. Google scraped this content and now serves it on its platform to keep users on Google because this exposes them to more ads and generates more ad revenue.

For those who think I’m anti-Google, here is what the creators of Google wrote almost 30 years ago:

The goals of the advertising business model do not always correspond to providing quality search to users. […] we expect that advertising funded search engines will be inherently biased towards the advertisers and away from the needs of the consumers. … But we believe the issue of advertising causes enough mixed incentives that it is crucial to have a competitive search engine that is transparent and in the academic realm.

— Sergey Brin and Larry Page, 1998

As this phenomenon of content theft increases, the click-through rate will keep decreasing for companies and publishers because content theft always leads to engagement theft. And more and more search consultants and growth advisors will continue to recommend moving away from Google Search as a reliable traffic source.

Google isn’t the only one that is transitioning: Individuals and businesses are also preparing their own transition to other channels and platforms. As this transition process accelerates for brands in the coming years, structured data will play a crucial role, first to keep your head out of the murky waters of Google’s unacceptable SERPs quality decrease but also to differentiate yourself on other platforms and in AI engines.

Schema was founded not only by Google but also by Microsoft (and others). OpenAI, in which Microsoft invested $13 billion, started using structured data. Officially, ChatGPT works on a giant neural network with probabilistic models and tokens, not tables or databases. So officially, no structured data… but you should soon see the visible results in ChatGPT.

And other LLMs will soon follow in my opinion.

In Google Search, structured data has an impact on rankings.

Contrary to the official statement, I’ve seen how structured data will make websites rank higher if implemented correctly.

Some SEOs might doubt my claims. But many SEOs implement very strange structured data. To me it looks unstructured. Sometimes the vocabulary they use does not exist. Sometimes they interconnect entities that aren’t trusted. Sometimes they seriously think that decent structured data can make up for low-quality content. Obviously, it is impossible to get better rankings with this approach. Why do I even have to write this? 😀

After reading my text, I hope you’ll take both my writings and all official Google statements with a giant bucket of salt. I know we should all remain skeptical regarding these topics but it is very hard when you’ve seen the real-world results 🙂

If you believe anything I wrote is wrong or misleading, please reach out. I’m always open to constructive criticism. I have strong opinions but I’m just an independent researcher who keeps testing. If you feel like roasting me on social networks, go for it: this meat 100% is organic! Just remain respectful and share counterarguments.

Here’s the downloadable PDF for those who want to read on a white background (below 2 Mb):

Google-is-WRONG-structured-data-impact-organic-rankings-Google-Search.pdf

© Elie Berreby – April 20, 2025 – First published on semking.com