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Microsoft and OpenAI signed a deal extending Microsoft’s rights to OpenAI models through 2032, confirming a 27% stake worth $135B
What does it say about the economics of content when the most visible site on the web loses significant traffic?
A status report by Wikipedia shows a significant decline in human page views over the last few months as a result of generative AI, “especially with search engines providing answers directly to searchers” [1].
Image Credit: Kevin IndigBoost your skills with Growth Memo’s weekly expert insights. Subscribe for free!
Wikipedia is an evergreen site. Even though it’s a user-generated content (UGC) platform like Reddit or YouTube, its primary purpose is to serve comprehensive definitions on established topics. Reddit, YouTube, and LinkedIn & Co. are about additive topics and insights.
AI destroys the value of one while raising it for the other.
Wikipedia’s human traffic has dipped -5% YoY, while scrapers grew by 10.5% and bots by 162.4% [2]. The fact that scrapers and bots together make up almost as much traffic as humans is symbolic of the eroding value of answering questions.
Even though Wikipedia’s direct traffic is up ~23% and Chat GPT referrals are up 3.5x YoY, Google referrals are down -35% because AI Overviews make it redundant for users to click through.
Image Credit: Kevin IndigOver the same time that Wikipedia lost ~90 million visits, Google started showing a lot more AI Overviews that answer user questions directly – often based on Wikipedia’s content.
Image Credit: Kevin IndigAlmost 50% of Wikipedia’s queries display a large AIO at the top of the search results. That’s no outlier: Reddit is at 46% and YouTube at 38%.
Google and ChatGPT reward additive content.
YouTube’s citation rate jumped from 37% to 54% (up 17 percentage points) at the same time as Wikipedia dropped from 58% to 42% (down 16 percentage points). Video is replacing text as Google’s primary source for answers.
Image Credit: Kevin IndigChatGPT cites Wikipedia 3x more often than it mentions the site, while Reddit is at one-to-one and YouTube at ~250%! Since users don’t click citations, mentions are much more valuable. [3]
Pre-AI, the economics of evergreen content were net-positive because it attracted clicks from Google, some of which converted into customers. LLMs like ChatGPT, AI Overviews, or AI Mode are not incentivized to send out traffic but to give the best answer, which makes the experience more similar to TikTok than Search.
LLMs use web content like Wikipedia for training, but offer invisible citations instead of mentions. The net return is negative. Wikipedia has to convince donors that it’s still worth giving money, while its content is used as a utility for LLMs.
Over the last 12 months, sites offering additive UGC have gained LLM visibility [4]:
At the same time, content sites offering evergreen content lost significant amounts of organic traffic (and value):
With fewer and eventually maybe zero clicks arriving [5], the value of creating evergreen content is questionable – not just for Wikipedia.
The fix is to shift focus from evergreen topics to net-new insights:
Evaluate additive content against influenced pipeline, LLM citations/mentions/Share of Voice, and publisher links/coverage.
Featured Image: Paulo Bobita/Search Engine Journal
This week’s Ask An SEO asks a classic content conundrum:
“Are content refreshes still an effective tactic, or is it better to create new pages altogether?”
Yes, content refreshes are still an effective tactic in cases such as:
With that said, not every page needs to be refreshed. If there is a similar topic that will help the reader but isn’t directly related to an existing header or sub-header, refreshing the page to include the new content could take your page off-topic. This can make it somewhat irrelevant or less helpful for users, which makes it bad for SEO, too. In this case, you’ll want to create a new page.
Once you have the new page created, look for where it can tie into the page you initially wanted to refresh and add an internal link to the new page. This gives the visitor on the page the opportunity to learn more or find the alternative, and then click back to finish reading or shopping. It also helps search engines and crawlers find their way to the new content.
New pages could be a good solution for:
For example, a recipe site that offers a regular, gluten-free, and vegetarian option doesn’t need to stuff all three recipe versions into the main recipe page. They can use an internal link at the top of the main recipe that says, “Click here for the gluten free version,” which helps the user and lets the search engines know they have this solution, too. Clothing brands can talk about tighter or looser fits and recommend a complementary brand if a customer complains about the same thing for a specific product or brand; this can go on product or category and collection pages.
If a client asks if they should refresh or create a new page, we:
Complicated pages are ones with:
But knowing what you could do or try doing doesn’t mean anything if you aren’t measuring the results.
Depending on which one you choose, you’ll have different ways to measure the effectiveness. Here are a few tests we do with clients in these same situations:
The first option is to have a control group with a couple of pages or topics, and we leave them alone as a control group. We then either expand with an equal amount of new content or refresh the same amount. The control group should be about as competitive to rank as the test groups, and from there, we watch over a few months to see if the test group begins climbing or gaining traffic while the control group remains the same.
The second test you can run, assuming you have a reasonably reliable rank tracking tool, is to monitor how many new keywords the content group has in the top 100 positions, top 20 positions, and top 10 positions after a couple of months. If the keywords and phrases have the same user intent as the topic (i.e., shopping vs. how to do something vs. informative and educational), then it looks like you made a good decision. On top of this, look for rich results like increases in People Also Ask and AI overview appearances. This is a sign the new content may be high quality and that you made the right decision.
I hope this helps answer your question. Refresh when the content is outdated, could be formatted better, or because it is fluffy and doesn’t provide value. Add new pages when there is a solution for a problem or an answer for a question, and it is unique enough from an existing page to justify the page’s existence. SEO keywords and search volumes do not justify this; an actual unique solution does.
More Resources:
Featured Image: Paulo Bobita/Search Engine Journal
Structured data helps search engines, Large Language Models (LLMs), AI assistants, and other tools understand your website. Using Schema.org and JSON-LD, you make your content clearer and easier to use across platforms. This guide explains what structured data is, why it matters today, and how you can set it up the right way.
Structured data is a way to tell computers exactly what’s on your web page. Using a standard set of tags from Schema.org, you can identify important details, like whether a page is about a product, a review, an article, an event, or something else.
This structured format helps search engines, AI assistants, LLMs, and other tools understand your content quickly and accurately. As a result, your site may qualify for special features in search results and can be recognized more easily by digital assistants or new AI applications.
Structured data is written in code, with JSON-LD being the most common format. Adding it to your pages gives your content a better chance to be found and understood, both now and as new technologies develop.
Read more: Schema, and why you need Yoast SEO to do it right »
Below is a simple example of structured data using Schema.org in JSON-LD format. This is a basic schema for a product with review properties. This code tells search engines that the page is a product (Product). It provides the name and description of the product, pricing information, the URL, plus product ratings and reviews. This allows search engines to understand your products and present your content in search results.
Product Title
Structured data gives computers a clear map of what’s on your website. It spells out details about your products, reviews, events, and much more in a format that’s easy for search engines and other systems to process.
This clarity leads to better visibility in search, including features like star ratings, images, or additional links. But the impact reaches further now. Structured data also helps AI assistants, voice search tools, and new web platforms like chatbots powered by Large Language Models understand and represent your content with greater accuracy.
New standards, such as NLWeb (Natural Language Web) and MCP (Model Context Protocol), are emerging to help different systems share and interpret web content consistently. Adding structured data today not only gives your site an advantage in search but also prepares it for a future where your content will flow across more platforms and digital experiences.
The effort you put into structured data now sets up your content to be found, used, and displayed in many places where people search and explore online.
Structured data plays a key role in how your website appears in search results. It helps search engines understand and present your content with extra features, such as review stars, images, and additional links. These enhanced listings can catch attention and drive more clicks to your site.
While using structured data doesn’t directly increase your rankings, it does make your site eligible for these rich results. That alone can set you apart from competitors. As search engines evolve and adopt new standards, well-structured data ensures your content stays visible and accessible in the latest search features.
For SEO, structured data is about making your site stand out, improving user experience, and giving your content the best shot at being discovered, both now and as search technology changes.
By describing your site for search engines, you allow them to do exciting things with your content. Schema.org and its support are constantly developing, improving, and expanding. As structured data forms the basis for many new developments in the SEO world, there will be more shortly. Below is an overview of the rich search results available; examples are in Google’s Search Gallery.
| Structured data type | Example use/description |
|---|---|
| Article | News, blog, or sports article |
| Breadcrumb | Navigation showing page position |
| Carousel | Gallery/list from one site (with Recipe, Course, Movie, Restaurant) |
| Course list | Lists of educational courses |
| Dataset | Large datasets (Google Dataset Search) |
| Discussion forum | User-generated forum content |
| Education Q&A | Education flashcard Q&As |
| Employer aggregate rating | Ratings about employers in job search results |
| Event | Concerts, festivals, and other events |
| FAQ | Frequently asked questions pages |
| Image metadata | Image creator, credit, and license details |
| Job posting | Listings for job openings |
| Local business | Business details: hours, directions, ratings |
| Math solver | Structured data for math problems |
| Movie | Lists of movies, movie details |
| Organization | About your company: name, logo, contact, etc. |
| Practice problem | Education practice problems for students |
| Product | Product listings with price, reviews, and more |
| Profile page | Info on a single person or organization |
| Q&A | Pages with a single question and answers |
| Recipe | Cooking recipes, steps, and ingredients |
| Review snippet | Short review/rating summaries |
| Software app | Ratings and details on apps or software |
| Speakable | Content for text-to-speech on Google Assistant |
| Subscription and paywalled content | Mark articles/content behind a paywall |
| Vacation rental | Details about vacation property listings |
| Video | Video info, segments, and live content |
You might have heard the term “rich snippets” before. Google now calls these enhancements “rich results.” Rich results are improved search listings that use structured data to show extra information, like images, reviews, product details, or FAQs, directly in search.
For example, a product page marked up with structured data can show its price, whether it’s in stock, and customer ratings right below the search listing, even before someone clicks. Here’s what that might look like:
With rich results, users see helpful details up front—such as a product’s price, star ratings, or stock status. This can make your listing stand out and attract more clicks.
Keep in mind, valid structured data increases your chances of getting rich results, but display is controlled by Google’s systems and is never guaranteed.
Keep reading: Rich snippets everywhere »
Results like this often appear more prominently on mobile devices. Search listings with structured data can display key information, like product prices, ratings, recipes, or booking options, in a mobile-friendly format. Carousels, images, and quick actions are designed for tapping and swiping with your finger.
For example, searching for a recipe on your phone might bring up a swipeable carousel showing photos, cooking times, and ratings for each dish. Product searches can highlight prices, availability, and reviews right in the results, helping users make decisions faster.
Many people now use mobile search as their default search method. Well-implemented structured data not only improves your visibility on mobile but can also make your content easier for users to explore and act on from their phones. To stay visible and competitive, regularly check your markup and make sure it works smoothly on mobile devices.
The Knowledge Graph Panel shows key facts about businesses, organizations, or people beside search results on desktop and at the top on mobile. It can include your logo, business description, location, contact details, and social profiles.
Using structured data, especially Organization, LocalBusiness, or Person markup with current details, helps Google recognize and display your entity accurately. Include recommended fields like your official name, logo, social links (using sameAs), and contact info.
Entity verification is becoming more important. Claim your Knowledge Panel through Google, and make sure your information is consistent across your website, social media, and trusted directories. Major search engines and AI assistants use this entity data for results, summaries, and answers, not just in search but also in AI-powered interfaces and smart devices.
While Google decides who appears in the Knowledge Panel and what details are shown, reliable structured data, verified identity, and a clear online presence give you the best chance of being featured.
Schema.org includes many types of structured data. You don’t need to use them all, just focus on what matches your site’s content. For example:
Before adding structured data, decide which parts of your site you want to highlight. Check Google’s or other search engines’ documentation to see which types are supported and what details they require. This helps ensure you are using the markup that will actually make your content stand out in search and other platforms.
Yoast SEO automatically adds structured data to your site using smart defaults, making it easier for search engines and platforms to understand your content. The plugin supports a wide range of content types, like articles, products, local businesses, and FAQs, without the need for manual schema coding.
With Yoast SEO, you can:
Yoast SEO also offers an extensible structured data platform. Developers can build on top of Yoast’s schema framework, add custom schema types, or connect other plugins. This helps advanced users or larger sites tailor their structured data for specific content, integrations, or new standards.
Yoast keeps pace with updates to structured data guidelines, so your markup stays aligned with what Google and other platforms support. This makes it easier to earn rich results and other search enhancements.
When adding structured data, focus first on the types that have the biggest impact on visibility and features in Google Search. These forms of schema are widely supported, trigger rich results, and apply to most kinds of sites:
When choosing which schema to add, always select types that match your site’s actual content. Refer to Google’s Search Gallery for the latest guidance and requirements for each type.
Adding the right structured data makes your pages eligible for rich results, enhances your visibility, and prepares your content for the next generation of search features and AI-powered platforms.
Read on: Local business listings with Schema.org and JSON-LD »
Voice search remains important, with a significant share of online queries now coming from voice-enabled devices. Structured data helps content be understood and, in some cases, selected as an answer for voice results.
The Speakable schema (for marking up sections meant to be read aloud by voice assistants) is still officially supported, but adoption is mostly limited to news content. Google and other assistants also use a broader mix of signals, like content clarity, authority, E-E-A-T, and traditional structured data, to power their spoken answers.
If you publish news or regularly answer concise, fact-based questions, consider using Speakable markup. For other content types, focus on structured data and well-organized, user-focused pages to improve your chances of being chosen by voice assistants. Voice search and voice assistants continue to draw on featured snippets, clear Q&A, and trusted sources.
Structured data uses Schema.org’s hierarchy. This vocabulary starts with broad types like Thing and narrows down to specific ones, such as Product, Movie, or LocalBusiness. Every type has its own properties, and more specific types inherit from their ancestors. For example, a Movie is a type of CreativeWork, which is a type of Thing.
When adding structured data, select the most specific type that fits your content. For a movie, this means using the Movie schema. For a local company, choose the type of business that best matches your offering under LocalBusiness.
Every Schema.org type includes a range of properties. While you can add many details, focus on the properties that Google or other search engines require or recommend for rich results. For example, a LocalBusiness should include your name, address, phone number, and, if possible, details such as opening hours, geo-coordinates, website, and reviews. You’ll find our Local SEO plugin (available in Yoast SEO Premium) very helpful if you need help with your local business markup.
Here are two examples of structures:
Movie hierarchy
Local business hierarchy
The more complete and accurate your markup, the greater your chances of being displayed with enhanced features like Knowledge Panels or map results. For details on recommended properties, always check Google’s up-to-date structured data documentation.
In the local business example, you’ll see that Google lists several required properties, like your business’s NAP (Name and Phone) details. There are also recommended properties, like URLs, geo-coordinates, opening hours, etc. Try to fill out as many of these as possible because search engines will only give you the whole presentation you want.
When you add structured data to your site, you’re not just identifying individual items, but you’re building a data graph. A graph in this context is a web of connections between all the different elements on your site, such as articles, authors, organizations, products, and events. Each entity is linked to others with clear relationships. For instance, an article can be marked as written by a certain author, published by your organization, and referencing a specific product. These connections help search engines and AI systems see the bigger picture of how everything on your site fits together.
Creating a fully connected data graph removes ambiguity. It allows search engines to understand exactly who created content, what brand a product belongs to, or where and when an event takes place, rather than making assumptions based on scattered information. This detailed understanding increases the chances that your site will qualify for rich results, Knowledge Panels, and other enhanced features in search. As your website grows, a well-connected graph also makes it easier to add new content or expand into new areas, since everything slots into place in a way that search engines can quickly process and understand.
With Yoast SEO, many of the key connections are generated automatically, giving your site a solid foundation. Still, understanding the importance of building a connected data graph helps you make better decisions when structuring your own content or customizing advanced schema. A thoughtful, well-linked graph sets your site up for today’s search features, while making it more adaptable for the future.
Structured data isn’t just about search results. It’s a map that helps AI assistants, knowledge graphs, and cross‑platform apps understand your content. It’s not just about showing a richer listing; it’s about enabling reliable AI interpretation and reuse across contexts.
Today, the primary payoff is still better search experiences. Tomorrow, AI systems and interoperable platforms will rely on clean, well‑defined data to summarize, reason about, and reuse your content. That shift makes data quality more important than ever.
Keep your structured data clean with a few simple habits. Use the same names for people, organizations, and products every time they appear across your site. Connect related information so search engines can see the links. For example, tie each article to its author or a product to its brand. Fill in all the key details for your main schema types and make sure nothing is missing. After making changes or adding new content, run your markup through a validation tool. If you add any custom fields or special schema, write down what they do so others can follow along later. Doing quick checks now and then keeps your data accurate and ready for both search engines and AI.
More and more, AI systems and search tools are looking for websites that are easy to understand, not just for people but also for machines. The Model Context Protocol (MCP) is gaining ground as a way for language models like Google Gemini and ChatGPT to use the structured data already present on your website. MCP draws on formats like Schema.org and JSON-LD to help AI match up the connections between things such as products, authors, and organizations.
Another project, the Natural Language Web (NLWeb), an open project developed by Microsoft, aims to make web content easier for AI to use in conversation and summaries. NLWeb builds on concepts like MCP, but hasn’t become a standard yet. For now, most progress and adoption are happening with MCP, and large language models are focusing their efforts on this area.
Using Schema.org and JSON-LD to keep your structured data clean (no duplicate entities), complete (all indexable content included), and connected (relationships preserved) will prepare you for search engines and new AI-driven features appearing across the web.
Schema.org and JSON-LD remain the foundation for structured data on the web. They enable today’s rich results in search and form the basis for how AI systems will interpret web content in the future. JSON-LD should be your default format for new markup, allowing you to build structured data graphs that are clean, accurate, and easy to maintain. Focus on accuracy in your markup rather than unnecessary complexity.
To future-proof your data, prioritize stable identifiers such as @id and use clear types to reduce ambiguity. Maintain strong connections between related entities across your pages. If you develop custom extensions to your structured data, document them thoroughly so both your team and automated tools can understand their purpose.
Design your schema so that components can be added or removed without disrupting the entire graph. Make a habit of running validations and audits after you change your site’s structure or content.
Finally, stay current by following guidance and news from official sources, including updates about standards such as NLWeb and MCP, to ensure your site remains compatible with both current search features and new interoperability initiatives.
To get the most value from structured data, focus first on the most important elements of your site. Describe the details that matter most for users and for search, such as your business information, your main products or services, reviews, events, or original articles. These core pieces of information are what search engines look for to understand your site and display enhanced results.
Rather than trying to mark up everything, start with the essentials that best match your content. As your experience grows, you can build on this foundation by adding more detail and creating links between related entities. Accurate, well-prioritized markup is both easier to maintain and more effective in helping your site stand out in search results and across new AI-driven features.
We’d like to remind you that Yoast SEO comes with an excellent structured data implementation. It’ll automatically handle most sites’ most pressing structured data needs. Of course, as mentioned below, you can extend our structured data framework as your needs become bigger.
Do the Yoast SEO configuration and get your site’s structured data set up in a few clicks! The configuration is available for all Yoast SEO users to help you get your plugin configured correctly. It’s quick, it’s easy, and doing it will pay off. Plus, if you’re using the new block editor in WordPress you can also add structured data to your FAQ pages and how-to articles using our structured data content blocks.
Thanks to JSON-LD, there’s nothing scary about adding the data to your pages anymore. This JavaScript-based data format makes it much easier to add structured data since it forms a block of code and is no longer embedded in the HTML of your page. This makes it easier to write and maintain, plus both humans and machines better understand it. If you need help implementing JSON-LD structured data, you can enroll in our free Structured Data for Beginners course, our Understanding Structured Data course, or read Google’s introduction to structured data.
JSON-LD is the recommended way to add structured data to your site. All major search engines, including Google and Bing, now fully support this format. JSON-LD is easy to implement and maintain, as it keeps your structured data separate from the main HTML.
Yoast SEO automatically creates a structured data graph for every page, connecting key elements like articles, authors, products, and organizations. This approach helps search engines and AI systems understand your site’s structure. Our developer resources include detailed Schema documentation and example graphs, making it straightforward to extend or customize your markup as your site grows.
Yoast SEO automatically handles much of the structured data in the background. You could extend our Schema framework, of course — see the next chapter –, but if adding code by hand seems scary, you could try some of the tools listed below. If you need help with how to proceed, ask your web developer for help. They will fix this for you in a couple of minutes.
Implementing structured data has always been challenging. Also, the results of most of those implementations often needed improvement. At Yoast, we set out to enhance the Schema output for millions of sites. For this, we built a Schema framework, which can be adapted and extended by anyone. We combined all those loose bits and pieces of structured data that appear on many sites, improved these, and put them in a graph. By interconnecting all these bits, we offer search engines all your connections on a silver platter.
See this video for more background on the schema graph.
Of course, there’s a lot more to it. We can also extend Yoast SEO output by adding specific Schema pieces, like how-tos or FAQs. We built structured data content blocks for use in the WordPress block editor. We’ve also enabled other WordPress plugins to integrate with our structured data framework, like Easy Digital Downloads, The Events Calendar, Seriously Simple Podcasting, and WP Recipe Maker, with more to come. Together, these help you remove barriers for search engines and users, as it has always been challenging to work with structured data.
A structured and focused approach is key to successful Schema.org markup on your website. Start by understanding Schema.org and how structured data can influence your site’s presence in search and beyond. Resources like Yoast’s developer portal offer useful insights into building flexible and future-proof markup.
Always use JSON-LD as recommended by Google, Bing, and Yoast. This format is easy to maintain and works well with modern websites. To maximize your implementation, use tools and frameworks that allow you to add, customize, and connect Schema.org data efficiently. Yoast SEO’s structured data framework, for example, enables seamless schema integration and extensibility across your site.
Validate your structured data regularly with tools like the Rich Results Test or Schema Markup Validator and monitor Google Search Console’s Enhancements reports for live feedback. Reviewing your markup helps you fix issues early and spot opportunities for richer results as search guidelines change. Periodically revisiting your strategy keeps your markup accurate and effective as new types and standards emerge.
By following the guidelines and adopting a comprehensive approach, you can successfully get structured data on your pages and enhance the effectiveness of your schema.org markup implementation for a robust SEO performance. Read the Yoast SEO Schema documentation to learn how Yoast SEO works with structured data, how you can extend it via an API, and how you can integrate it into your work.
Keep on reading: Open-source software, open Schema protocol! »
Structured data has become an essential part of building a visible, findable, and adaptable website. Using Schema.org and JSON-LD not only helps search engines understand your content but also sets your site up for better performance in new AI-driven features, rich results, and across platforms.
Start by focusing on the most important parts of your site, like business information, products, articles, or events, and grow your structured data as your needs evolve. Connected, well-maintained markup now prepares your site for search, AI, and whatever comes next in digital content.
Explore our documentation and training resources to learn more about best practices, advanced integrations, or how Yoast SEO can simplify structured data. Investing the time in good markup today will help your content stand out wherever people (or algorithms) find it.
Read more: How to check the performance of your rich results in Google Search Console »
Google’s John Mueller answered a question about canonicals, expressing his opinion that “hope” shouldn’t be a part of your SEO strategy with regard to canonicals. The implication is that hoping Google will figure it out on its own misses the point of what SEO is about.
Rel=canonical is an HTML tag that enables a publisher or SEO to tell Google what their preferred URL is. For example, it’s useful for suggesting the best URL when there are multiple URLs with the same or similar content. Google isn’t obligated to obey the rel=canonical declaration, it’s treated as a strong hint.
Someone on Reddit was in the situation where a website has category names that they begin with a capitalized letter but the canonical tag contains a lowercase version. There is currently a redirect from the lowercase version to the uppercase.
They’re currently not seeing any negative impact from this state of the website and were asking if it’s okay to leave it as-is because it hasn’t affected search visibility.
The person asking the question wrote:
“…I’m running into something annoying on our blog and could use a sanity check before I push dev too hard to fix it. It’s been an issue for a month, after a redesign was launched.
All of our URLs resolve in this format: /site/Topic/topic-title/
…but the canonical tag uses a lowercase topic, like: /site/topic/topic-title/
So the canonical doesn’t exactly match the actual URL’s case. Lowercase topic 301 redirects to the correct, uppercase version.
I know that mismatched canonicals can send mixed signals to Google.
Dev is asking, “Are you seeing any real impact from this?” and technically, the answer is no — but I still think it’s worth fixing to follow best practices.”
This is an interesting case because in many things related to SEO if something’s working there’s little point trying to fix a small detail for fear of triggering a negative response. Relying on Google to figure things out is another fallback.
Google’s John Mueller has a different opinion. He responded:
“URL path, filename, and query parameters are case-sensitive, the hostname / domain name aren’t. Case-sensitivity matters for canonicalization, so it’s a good idea to be consistent there. If it serves the same content, it’ll probably be seen as a duplicate and folded together, but “hope” should not be a part of an SEO strategy.
Case-sensitivity in URLs also matters for robots.txt.”
I know that in highly competitive niches the SEO is on a generally flawless level. If there’s something to improve it gets improved. And there’s a good reason for that. Someone at one of the search engines once told me that anything you can do to make it easier for the crawlers is a win. They advised me to make sites easy to crawl and content easy to understand. That advice is still useful, it follows with Mueller’s advice to not “hope” that Google figures things out, implying that it’s best to make sure they do work out.
Featured Image by Shutterstock/MyronovDesign
Let’s reminisce for a moment. Do you remember how, back in 2020, we all obsessed over “link juice” and PageRank flow as far as internal links are concerned?
In 2025, what matters more is how your internal links define the entities and relationships on your site.
Internal linking is no longer just about distributing authority. It’s about:
The last full guide I wrote on internal linking strategies was in 2020, and – well – much has happened since then (to say the least).
And most internal linking guides treat links as simple “traffic routers,” ignoring their role in building entity context.
So today, yes, I’m revisiting some of the basic building blocks of SEO, but we’re going to expand how we think about internal linking.
If you’re already deep into entity-first SEO and apply it to your internal linking tactics, skip ahead to the action items to ensure you’re implementing it well.
For everyone else, I’ll explain why tightening up your internal linking structure isn’t just table stakes. It’s one of the simplest core levers to influence organic visibility.
Image Credit: Kevin IndigBoost your skills with Growth Memo’s weekly expert insights. Subscribe for free!
Internal linking is the age-old SEO practice of connecting one page on your site to another page, all on the same domain.
These links act like the roads or highways that guide users through your content. But they also help search engines understand how your pages relate.
In the past, we thought about internal links as “pipes” for PageRank.
Add enough links from your homepage or other strong, well-ranking pages, and you’d push authority toward the URLs you wanted to rank.
That view isn’t wrong; it’s just incomplete.
Today, internal links aren’t just distributing authority. They’re defining the semantic structure of your site.
Internal linking isn’t simply a practice that routes people (and bots/crawlers) to the pages you want them to go to.
In fact, when we think about internal linking this way is exactly when we start to half-ass the practice or let it sit on the back burner.
The words you use in anchor text and the way you connect hubs of related content all signal to search engines: These are the entities your brand wants to be known for.
Strategic internal linking can do three critical things for your site:
Put simply: Internal links aren’t just SEO plumbing. They’re how you build a discoverable, authoritative entity graph inside your own site.
Generative AI being infused into all modalities of search means Google and LLMs aren’t just hiking all over the web searching for crawlable/indexable pages — search engines and LLMs are mapping relationships between entities and judging your brand’s authority accordingly.
But currently, there’s some disagreement on whether or not LLMs can navigate your site through internal links.
My hypothesis? LLMs do form entity relationships via your strategic use of internal links. But probably not through traditionally “crawling” them like search engines do, and more purely based on text signals on the page.
And if that turns out to be true – keeping in mind that LLMs often use search engine results to ground themselves – internal linking also benefits LLM optimization/AEO/GEO mostly by improving Google/Bing ranks, which LLMs heavily rely on.
I dropped the question over on LinkedIn, you can check out the discussion there. But a few responses stood out. (Take a look at the full thread, but I also highly recommend following these pros to learn more from each of them.)
Dan Petrovic, founder and CEO of Dejan SEO, gave a detailed answer about the differences between a) the types of LLM crawlers and b) the different LLMs and how they behave.
Image Credit: Kevin IndigLily Grozeva, head of SEO at Verto Digital, rightfully called out that we can all get the answer in our own logfiles.
Image Credit: Kevin IndigChee Lo, head of SEO at Trustpilot, shared his experience with Perplexity, which seems to be a bit more aggressive than other bots.
Image Credit: Kevin IndigSites with clear internal linking patterns that mirror how humans connect concepts are (in theory, more data will tell over time) better positioned to be included in AI-generated answers and entity-rich snippets.
Way back in 2019, I explained the following in Semantic content optimization with entities:
Entities are semantic, interconnected objects that help machines to understand explicit and implicit language. In simpler terms, they are words (nouns) that represent any type of object, concept, or subject … According to Cindy Krum and her fantastic entity series, Google seems to restructure its whole approach to indexing based on entities (while you’re at it, read AJ Kohn’s article about embeddings). Understanding entities and how Google uses them in search sharpens our standards for content creation, optimization, and the use of schema markup.
Entities are nouns like events, ideas, people, places, etc. They’re the building blocks of ideas and how those ideas relate to each other. (They’re not just “keywords.”)
Search engines and LLMS use semantic relationships between entities to (1) reduce ambiguity, (2) reinforce authority/canonical sources on your site, and (3) map out relationships between topics, features, services, and audiences across your site.
When you internally link pages together with strategically descriptive anchors, you’re telling search engines how your site fits together … and you’re training them on how entities across your site connect.
Therefore, by practicing internal linking through an entity-based lens, you’re creating stronger, clearer relationships and patterns for Google/search engines/LLMs to understand.
Entity-first SEO starts with defining the people, products, concepts, and places your brand “owns.”
If you’re a B2B SaaS company offering a CRM, those entities might include your:
Taking this example, you’re going to think in terms of topic-first SEO:
For example, look at this topic cluster map created with Screaming Frog:
Image Credit: Kevin IndigIt shows two clusters with nodes very close together (red and orange) and three other clusters that are spread apart (green, blue, and purple). Guess which clusters outperform the others in organic search? Red and orange!
Here’s how you connect those entities into a meaningful structure in the copy on the page:
1. Anchor text = entity disambiguation.
Instead of linking with vague text, use descriptive anchors that clarify which entity the link refers to. For example, if your CRM has a feature page about pipeline management, link to it with “sales pipeline management CRM feature” language.
2. Consistency matters.
If you always link to that pipeline management page with variations like “pipeline automation tool,” “deal tracking software,” and “CRM feature,” you dilute the entity connection. (But variations like “pipeline management tool,” “sales pipeline management CRM feature,” and “pipeline management features” are derivatives.)
By sticking to clear, consistent anchors, you signal to Google that this is the page that defines “pipeline management” for your brand.
3. Context strengthens meaning.
The sentence or paragraph around the link can add semantic weight. For example:
“Our CRM includes pipeline management, so your sales team can track every deal from prospecting to close.”
That tells Google (and users) that pipeline management isn’t just a phrase; it’s a core feature within the CRM product.
4. Include personas.
Making personas a criterion for internal linking is a no-brainer, because from a psychological perspective, a link automatically signals “there’s more for you here.”
If your internal link is placed on the right word that triggers a response in your target ICPs (and the right areas of the page), it increases the chance of people staying on the site. It’s also just a better experience – and good customer service – to help site visitors find the right offering specifically for themselves, all with the goal to increase trust and the chances they take an action or convert.
If one of your ICPs is head of Sales at mid-market SaaS companies, you might internally link from a blog article like “10 Ways SaaS Sales Leaders Can Shorten Their Sales Cycle” directly to your pipeline management feature page, while using copy surrounding that link that explains how your offering solves this problem. That link makes the relationship explicit: This is the feature that solves this persona’s pain point.
Ultimately, think of every internal link as a connector in your brand’s knowledge graph.
Together, these links show how entities and topics (like CRM platform → pipeline management → sales enablement → head of sales persona) relate to each other, and why your site is authoritative on them.
Amanda Johnson jumping in here to add: Basically, show + tell people (and search engines/LLMs) what you want them to know via literal semantics. It really is that simple. No need to overthink this. Use clear, descriptive, accurate anchor text for the internally linked page, use it consistently, and give context as to how/why the page is linked there with surrounding copy.
Ultimately, if you practice internal linking thoughtfully and methodically, you end up with a better user experience and more thorough reinforcement of internal entity relationships (which can improve topical authority signals).
Worried that your most important pages aren’t getting enough visibility because you haven’t set up a clear linking structure? Following the guidance above will help you resolve this and set up a clear internal linking system.
And using tools that have internal link auditing (like Semrush, Ahrefs, Clearscope, Surfer, etc.) will help you implement your system. Some SEO tools also give page-level internal linking recommendations and copy suggestions to anchor the text to.
Internal linking hasn’t just been about crawlability for some time now.
By structuring links around topics, entities, (and even user journeys of your target personas), you communicate your site’s semantic map to Google and LLMs.
Featured Image: Paulo Bobita/Search Engine Journal
OpenAI rolled out a new web browser last week called Atlas. It comes with ChatGPT built in, along with an agent, so that you can browse, get direct answers, and have automated tasks performed on your behalf all at the same time.
I’ve spent the past several days tinkering with Atlas. I’ve used it to do all my normal web browsing, and also tried to take advantage of the ChatGPT functions—plus I threw some weird agentic tasks its way to see how it did with those. And my impression is that Atlas is… fine? But my big takeaway is that it’s pretty pointless for anyone not employed by OpenAI, and that Atlas is little more than cynicism masquerading as software.
If you want to know why, let’s start by looking at its agentic capabilities—which is really where it differentiates.
When I was browsing Amazon, I asked the Atlas agent to do some shopping for me, using a pre-set prompt of its own suggestion. (“Start a cart with items I’m likely to want based on my browsing here and highlight any active promo codes. Let me review before checkout.”) It picked out a notebook that I’d recently purchased and no longer needed, some deodorant I’d recently purchased and no longer needed, and a vacuum cleaner that I’d considered but decided was too expensive and no longer needed because I bought a cheaper one.
I would guess that it took 10 minutes or so for it to do all that. I cleaned out my cart and considered myself lucky that it didn’t buy anything.
When I logged onto Facebook, which is already lousy with all sorts of AI slop, I asked it to create a status update for me. So it dug through my browser history and came back with an incredibly long status I won’t bore you with all of it (and there was a lot) but here are the highlights from what it suggested: “I dipped into Smartsheet and TeamSnap (because editors juggle rosters too!), flirted with Shopify and Amazon (holiday gift‑shopping? side hustle? you decide), and kept tabs on the news … . Somewhere in there I even remembered to log into Slack, schedule Zoom meetings, and read a few NYTimes and Technology Review pieces. Who says an editor’s life isn’t glamorous? 
”
Uh. Okay. I decided against posting that. There were some other equally unillustrious examples as well, but you get the picture.
Aside from the agent, the other unique feature is having ChatGPT built right into the browser. Notice I said “unique,” not “useful.” I struggled with finding any obvious utility by having this right there, versus just going to chatgpt dot com. In some cases, the built-in chatbot was worse and dumber.
For example, I asked the built-in ChatGPT to summarize a MIT Technology Review article I was reading for me. Yet instead of answering the question about the page I was on, it referred back to the page I had previously been on when I started the session. Which is to say it spit back some useless nonsense. Thanks, AI.
OpenAI is marketing Atlas pretty aggressively when you come to ChatGPT now, suggesting people download it. And it may in fact score a lot of downloads because of that. But without giving people more of a reason to actually switch from more entrenched browsers, like Chrome or Safari, this feels like a real empty salvo in the new browser wars.
It’s been hard for me to understand why Atlas exists. Who is this browser for, exactly? Who is its customer? And the answer I have come to there is that Atlas is for OpenAI. The real customer, the true end user of Atlas, is not the person browsing websites, it is the company collecting data about what and how that person is browsing.
This review first appeared in The Debrief, Mat Honan’s weekly subscriber-only newsletter.
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
I tried OpenAI’s new Atlas browser but I still don’t know what it’s for
—Mat Honan
OpenAI rolled out a new web browser last week called Atlas. It comes with ChatGPT built in, along with an agent, so that you can browse, get answers, and have automated tasks performed on your behalf all at the same time.
I’ve spent the past several days tinkering with Atlas. I’ve used it to do all my normal web browsing, and also tried to take advantage of the ChatGPT functions—plus I threw some weird agentic tasks its way to see how it did with those.
My impression is that Atlas is… fine? But my big takeaway is that it’s pretty pointless for anyone not employed by OpenAI. In fact, Atlas seems to be little more than cynicism masquerading as software. Read the full story.
This review first appeared in The Debrief, Mat Honan’s weekly subscriber-only newsletter.
Seeking climate solutions in turbulent times
Despite recent political shifts in the US, companies are continuing to pursue exciting new climate solutions. Tomorrow we’re holding an exclusive subscriber-only Roundtable event digging into the most promising technologies of the moment drawing from our recently released 10 Climate Tech Companies to Watch list.
This conversation will give subscribers insight into where tangible climate progress is happening today, and how recent political changes are reshaping the path toward a more sustainable future. Join us at 1pm ET on Tuesday October 28—register here!
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Donald Trump says a TikTok deal could be reached this week
Perhaps on Thursday, when he’s due to meet Xi Jinping. (CNBC)
+ US treasury secretary Scott Bessent appeared to jump the gun when he said the deal had already been done. (The Guardian)
2 Covid vaccines helped to prolong the life of cancer patients
The findings raise hopes a universal vaccine could help patients with different cancers. (WP $)
+ Why US federal health agencies are abandoning mRNA vaccines. (MIT Technology Review)
3 How developing nations benefit from “AI decolonization”
Rules forcing Silicon Valley’s giants to process data locally has helped to spread the AI boom’s wealth. (WSJ $)
+ Meanwhile, Saudi Arabia wants to be known as the “AI exporter.” (NYT $)
+ Inside India’s scramble for AI independence. (MIT Technology Review)
4 Those rising electricity costs aren’t just down to AI
Costly electrical equipment and disaster prep are bigger factors pushing up prices. (WP $)
+ Amazon considered concealing its data centers’ water usage. (The Guardian)
+ AI is changing the grid. Could it help more than it harms? (MIT Technology Review)
5 California State wants to become America’s largest “AI-empowered” University
It’s teaming up with Amazon, OpenAI and Nvidia to prepare its students for increasingly AI-driven careers. (NYT $)
+ How do technologies change our abilities to learn skills? (The Atlantic $)
+ Why the ultra-wealthy are sending their kids to High Point University. (WSJ $)
+ The job market is tough right now, but we’ve weathered this kind of storm before. (Insider $)
6 This new startup sells AI bot interactions to manipulate social media
Even though it violates every major platforms’ policies. (404 Media)
7 Even real estate isn’t safe from AI slop 
House hunters are being forced to wade through AI-enhanced listings. (Wired $)
8 Why we’re so obsessed with sleepmaxxing
Yes, sleep is good for you. But does the tech that tracks it really do the job it claims to? (The Atlantic $)
+ I tried to hack my insomnia with technology. Here’s what worked. (MIT Technology Review)
9 It’s probably not worth buying an Ultra-HD TV
So feel free to ignore all that persuasive marketing jargon. (The Guardian)
10 Sneaky employees are using AI to fake their expense receipts 
So expense firms are in turn deploying AI to try and detect the fakes. (FT $)
Quote of the day
“I’m skeptical of all of the hype around AI right now. This is not my first bubble.”
—Jay Goldberg, a senior analyst at Seaport Global Securities, is no stranger to the hysteria that surrounds overhyped technologies, he tells Bloomberg.
One more thing
Inside Clear’s ambitions to manage your identity beyond the airport
Clear Secure is the most visible biometric identity company in the United States. Best known for its line-jumping service in airports, it’s also popping up at sports arenas and stadiums all over the country. You can also use its identity verification platform to rent tools at Home Depot, put your profile in front of recruiters on LinkedIn, and, as of this month, verify your identity as a rider on Uber.
And soon enough, if Clear has its way, it may also be in your favorite retailer, bank, and even doctor’s office—or anywhere else that you currently have to pull out a wallet (or wait in line).
While the company has been building toward this sweeping vision for years, it now seems its time has finally come. But as biometrics go mainstream, what—and who—bears the cost? Read the full story.
—Eileen Guo
We can still have nice things
A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.)
+ Ancient manuscripts are jam packed with weird and wonderful beasts.
+ Horror writers tell us the spooky stories that send a shiver down their respective spines.
+ Here’s why living on a red dwarf isn’t quite as crazy as it sounds.
+ Kiki the sheep may not be able to walk, but she isn’t letting it get in the way of her getting around 
(thanks Amy!)
Google and Bing publish guidelines for traditional search engine optimization and provide tools to measure performance.
We have no such instruction from generative engine providers, making optimization much more challenging. The result is a slew of misleading and uninformed speculation.
The importance of Schema.org markup is an example.
I’ve seen no statement or indication from a large language model regarding structured data markup, including Schema.org’s.
Google has long advised using such markup for traditional organic search, stating:
Google Search works hard to understand the content of a page. You can help us by providing explicit clues about the meaning of a page to Google by including structured data on the page.
The search giant generates rich snippets from select structured data and gathers info on a business from additional markup types, such as Schema.org’s Organization, FAQPage, and Author.
While answers from Google’s AI Mode tend to come from top organic rankings, we don’t know the impact of structured data on AI agents or crawlers.
Unlike Google, LLMs have no native indexes. They generate answers based on their training data (which doesn’t store URLs or code) and from external search engines such as Google, Bing, Reddit, and YouTube.
To access a page, LLMs can (i) query traditional search engines, indirectly relying on structured data markup such as Schema.org, and (ii) crawl a page directly to fetch answers.
Many businesses don’t understand Schema.org markup, and thus retain the GEO services that claim implementing it will increase AI visibility.
Don’t be misled. I’ve seen no reputable case studies demonstrating that structured data improves AI mentions or citations. Implementation, moreover, is easy (and cheap) with apps and plugins.
Instead, focus on the proven long-term tactics:
Structured data markup such as Schema.org likely drives organic search rankings and therefore helps AI visibility indirectly. Yet implementation is easy and almost certainly a low priority. What really matters for AI visibility is relevant content and long-term brand building.
YouTube launched Ask Studio, an AI assistant built into YouTube Studio that analyzes channel data to provide insights and content suggestions.
The tool appears as a chat interface accessed through a sparkle icon in YouTube Studio. You can ask for comment summaries, video performance analysis, and content ideas based on your channel’s data.
Ask Studio analyzes three primary types of channel data: comments, analytics, and past content performance.
For comments, Ask Studio can summarize key themes and sentiment across videos. You can ask for summaries on a specific video or get an overall view of what viewers are talking about.
For analytics, Ask Studio pulls from the same performance metrics already in YouTube Studio. It identifies patterns and suggests areas for improvement based on the channel’s data.
For content planning, Ask Studio can generate ideas tailored to what viewers already respond to. You can prompt it for new angles on an ongoing series, ask what topics are resonating with your audience, or get title and outline suggestions.
See a full walkthrough in the video below:
Ask Studio and the Inspiration Tab are both designed to help with content ideas, but they work differently.
Inspiration Tab is a visual surface. It shows idea cards, images, and thumbnail suggestions for creators who like to browse concepts.
Ask Studio is conversational. You type a prompt and get an answer in plain language. It’s meant for creators who already have a direction and want help sharpening the angle, planning the next video, or understanding what viewers are saying.
Both use your channel data, but Ask Studio responds in real time. Inspiration Tab curates pre-generated suggestions.
Ask Studio is currently available in English to a limited group of creators in the United States.
YouTube says it’s continuing to expand access to more U.S. creators, experimenting with additional languages, and working on international rollout.
Some prompts may return a generic response or “I can’t help with that.” YouTube says that happens when Ask Studio doesn’t have enough context or doesn’t support that request yet.
Ask Studio can surface patterns in your comments and analytics without manually digging through dashboards or scrolling hundreds of viewer messages. That reduces the time spent on reporting and lets you focus on packaging the next video.
The current limitation is reach. Right now it’s U.S.-only, English-only, and only some channels are in the test group, which restricts access for international creators and teams that work across multiple languages.
YouTube says it plans to roll out Ask Studio to more creators in the United States before expanding internationally. The company is also testing additional language support but hasn’t announced specific languages or dates.
The launch continues YouTube’s push toward AI-assisted creator tools inside YouTube Studio, alongside features like the Inspiration Tab for idea generation.
Featured Image: vrlibsstudio/Shutterstock