Today’s Memo is a full refresh of one of the most important frameworks I use with clients – and one I’ve updated heavily based on how AI is reshaping search behavior…

…I’m talking about the keyword universe. 🪐

In this issue, I’m digging into:

• Why the old way of doing keyword research doesn’t cut it anymore.
• How to build a keyword pipeline that compounds over time.
• A scoring system for prioritizing keywords that actually convert.
• How to handle keyword chaos with structure and clarity.
• A simple keyword universe tracker I designed that will save you hours of trial and error (for premium subscribers).

Initiating liftoff … we’re heading into search space. 🧑‍🚀🛸

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A single keyword no longer represents a single intent or SERP outcome. In today’s AI-driven search landscape, we need scalable structures that map and evolve with intent … not just “rank.”

Therefore, the classic approach to keyword research is outdated.

In fact, despite all the boy-who-cried-wolf “SEO is dead!” claims across the web, I’d argue that keyword-based SEO is actually dead, which I wrote about in Death of the Keyword.

And it has been for a while.

But the SEO keyword universe is not. And I’ll explain why.

What A Keyword Universe Is – And Why You Need It

A keyword universe is a big pool of language your target audience uses when they search that will help them find you.

It surfaces the most important queries and phrases (i.e., keywords) at the top and lives in a spreadsheet or database, like BigQuery.

Instead of hyperfocusing on specific keywords or doing a keyword sprint every so often, you need to build a keyword universe that you’ll explore and conquer across your site over time.

One problem I tried to solve with the keyword universe is that keyword and intent research is often static.

It happens maybe every month or quarter, and it’s very manual. A keyword universe is both static and dynamic. While that might sound counterintuitive, here’s what I mean:

The keyword universe is like a pool that you can fill with water whenever you want. You can update it daily, monthly, quarter – whenever. It always surfaces the most important intents at the top.

For the majority of brands, some keyword-universe-building tasks only need to be done once (or once on product/service launch), while other tasks might be ongoing. More on this below.

Within your database, you’ll assign weighted scores to prioritize content creation, but that scoring system might shift over time based on changes in initiatives, product/feature launches, and discovering topics with high conversion rates.

To Infinity And Beyond

The goal in building your keyword universe is to create a keyword pipeline for content creation – one that you prioritize by business impact.

Keyword universes elevate the most impactful topics to the top of a list, which allows you to focus on planning capacity, like:

• The number of published articles needed to comprehensively cover core topics.
• Resources needed to cover essential topics in a competitive timeframe.
• Roadmapping content formats and angles (e.g., long-form guides, comparison tables, videos, etc.).

A big problem in SEO is knowing which keywords convert to customers before targeting them.

One big advantage of the keyword universe (compared to research sprints) is that new keywords automatically fall into a natural prioritization.

And with the advent of AI in search, like AI Overviews/Google’s AI Mode, this is more important than ever.

The keyword universe mitigates that problem through a clever sorting system.

SEO pros can continuously research and launch new keywords into the universe, while writers can pick keywords off the list at any time.

Think fluid collaboration.

Keyword universes are mostly relevant for companies that have to create content themselves instead of leaning on users or products. I call them integrators.

Typical integrator culprits are SaaS, DTC, or publishing businesses, which often have no predetermined, product-led SEO structure for keyword prioritization.

The opposite is aggregators, which scale organic traffic through user-generated content (UGC) or product inventory. (Examples include sites like TripAdvisor, Uber Eats, TikTok, and Yelp.)

The keyword path for aggregators is defined by their page types. And the target topics come out of the product.

Yelp, for example, knows that “near me keywords” and query patterns like “{business} in {city}” are important because that’s the main use case for their local listing pages.

Integrators don’t have that luxury. They need to use other signals to prioritize keywords for business impact.

Ready To Take On The Galaxy? Build Your Keyword Universe

Creating your keyword universe is a three-step process.

And I’ll bet it’s likely you have old spreadsheets of keywords littered throughout your shared drives, collecting dust.

Guess what? You can add them to this process and make good use of them, too. (Finally.)

Step 1: Mine For Queries

Keyword mining is the science of building a large list of keywords and a bread-and-butter workflow in SEO.

The classic way is to use a list of seed keywords and throw them into third-party rank trackers (like Semrush or Ahrefs) to get related terms and other suggestions.

That’s a good start, but that’s what your competitors are doing too.

You need to look for fresh ideas that are unique to your brand – data that no one else has…

…so start with customer conversations.

Dig into:

• Sales calls.
• Support requests.
• Customer and/or target audience interviews.
• Social media comments on branded accounts.
• Product or business reviews.

And then extract key phrasing, questions, and terms your audience actually uses.

But don’t ignore other valuable sources of keyword ideas:

• SERP features, like AIOs, PAAs, and Google Suggest.
• Search Console: keywords Google tries to rank your site for.
• Competitor ranks and paid search keywords.
• Conversational prompts your target audience is likely to use.
• Reddit threads, YouTube comments, podcast scripts, etc.

The goal of the first step is to grow our universe with as many keywords as we can find.

(Don’t obsess over relevance. That’s Step 2.)

During this phase, there are some keyword universe research tasks that will be one-time-only, and some that will likely need refreshing or repeating over time.

Here’s a quick list to distinguish between repeat and one-time tasks:

1. Audience-based research: Repeat and refresh over time – quarterly is often sufficient. Pay attention to what pops up seasonally.
2. Product-focused research: Complete for the initial launch of a new product or feature.
3. Competitor-focused research: Complete once for both business and SEO competitors. Refresh/update when there’s a new feature, product/service, or competitor.
4. Location-focused research: Do this once per geographic location serviced and when you expand into new service locations

Step 2: Sort And Align

Step 2, sorting the long list of mined queries, is the linchpin of keyword universes.

If you get this right, you’ll be installing a powerful SEO prioritization system for your company.

Getting it wrong is just wasting time.

Anyone can create a large list of keywords, but creating strong filters and sorting mechanisms is hard.

The old school way to go about prioritization is by search volume.

Throw that classic view out the window: We can do better than that.

Most times, keywords with higher search volume actually convert less well – or get no real traffic at all due to AIOs.

As I mentioned in Death of the Keyword:

A couple of months ago, I rewrote my guide to inhouse SEO and started ranking in position one. But the joke was on me. I didn’t get a single dirty click for that keyword. Over 200 people search for “in house seo” but not a single person clicks on a search result.

By the way, Google Analytics only shows 10 clicks from organic search over the last 3 months. So, what’s going on? The 10 clicks I actually got are not reported in GSC (privacy… I guess?), but the majority of searchers likely click on one of the People Also Asked features that show up right below my search result.

Keeping that in mind about search volume, since we don’t know which keywords are most important for the business before targeting them – and we don’t want to make decisions by volume alone – we need sorting parameters based on strong signals.

We can summarize several signals for each keyword and sort the list by total score.

That’s exactly what I’ve done with clients like Ramp, the fastest-growing fintech startup in history, to prioritize content strategy.

Sorting is about defining an initial set of signals and then refining it with feedback.

You’ll start by giving each signal a weight based on our best guess – and then refine it over time.

When you build your keyword universe, you’ll want to define an automated logic (say, in Google Sheets or BigQuery).

Your logic could be a simple “if this then that,” like “if keyword is mentioned by customer, assign 10 points.”

Potential signals (not all need to be used):

• Keyword is mentioned in customer conversation.
• Keyword is part of a topic that converts well.
• Topic is sharply related to direct offering or pain point your brand solves.
• Mmonthly search volume (MSV)
• Keyword difficulty (KD)/competitiveness
• (MSV * KD) / CPC → I like to use this simple formula to balance search demand with competitiveness and potential conversion value.
• Traffic potential.
• Conversions from paid search or other channels.
• Growing or shrinking MSV.
• Query modifier indicates users are ready to take action, like “buy” or “download.”

You should give each signal a weight from 0-10 or 0-3, with the highest number being strongest and zero being weakest.

Your scoring will be unique to you based on business goals.

Let’s pause here for a moment: I created a simple tool that will make this work way easier, saving a lot of time and trial + error. (It’s below!) Premium subscribers get full access to tools like this one, along with additional content and deep dives.

But let’s say you’re prioritizing building content around essential topics and have goals set around growing topical authority. And let’s say you’re using the 0-10 scale. Your scoring might look something like:

• Keyword is mentioned in customer conversation: 10.
• Keyword is part of a topic that converts well: 10.
• Topic is sharply related to direct offering or pain point your brand solves: 10.
• MSV: 3.
• KD/competitiveness: 6.
• (MSV * KD) / CPC → I like to use this simple formula to balance search demand with competitiveness and potential conversion value: 5.
• Traffic potential: 3.
• Conversions from paid search or other channels: 6.
• Growing or shrinking MSV: 4.
• Query modifier indicates users are ready to take action, like “buy” or “download”: 7.

The sum of all scores for each query in your universe then determines the priority sorting of the list.

Keywords with the highest total score land at the top and vice versa.

New keywords on the list fall into a natural prioritization.

Important note: If your research shows that sales are connected to queries related to current events, news, updates in research reports, etc., those should be addressed as soon as possible.

(Example: If your company sells home solar batteries and recent weather news increases demand due to a specific weather event, make sure to prioritize that in your universe ASAP.)

Amanda’s thoughts: I might get some hate for this stance, but if you’re a new brand or site just beginning to build a content library and you fall into the integrator category, focus on building trust first by securing visibility in organic search results where you can as quickly as you can.

I know, I know: What about conversions? Conversion-focused content is crucial to the long-term success of the org.

But to set yourself apart, you need to actually create the content that no one is making about the questions, pain points, and specific needs your target audience is voicing.

If your sales team repeatedly hears a version of the same question, it’s likely there’s no easy-to-find answer to the question – or the current answers out there aren’t trustworthy. Trust is the most important currency in the era of AI-based search. Start building it ASAP. Conversions will follow.

Step 3: Refine

Models get good by improving over time.

Like a large language model that learns from fine-tuning, we need to adjust our signal weighting based on the results we see.

We can go about fine-tuning in two ways:

1. Anecdotally, conversions should increase as we build new content (or update existing content) based on the keyword universe prioritization scoring.

Otherwise, sorting signals have the wrong weight, and we need to adjust.

2. Another way to test the system is a snapshot analysis.

To do so, you’ll run a comparison of two sets of data: the keywords that attract the most organic visibility and the pages that drive the most conversions, side-by-side with the keywords at the top of the universe.

Ideally, they overlap. If they don’t, aim to adjust your sorting signals until they come close.

Tips For Maintaining Your Keyword Universe

Look, there’s no point in doing all this work unless you’re going to maintain the hygiene of this data over time.

This is what you need to keep in mind:

1. Once you’ve created a page that targets a keyword in your list, move it to a second tab on the spreadsheet or another table in the database.

That way, you don’t lose track and end up with writers creating duplicate content.

2. Build custom click curves for each page type (blog article, landing page, calculator, etc.) when including traffic and revenue projections.

Assign each step in the conversion funnel a conversion rate – like visit ➡️newsletter sign-up, visit ➡️demo, visit ➡️purchase – and multiply search volume with an estimated position on the custom click curve, conversion rates, and lifetime value. (Fine-tune regularly.)

Here’s an example: MSV * CTR (pos 1) * CVRs * Lifetime value = Revenue prediction

3. GPT for Sheets or the Meaning Cloud extension for Google Sheets can speed up assigning each keyword to a topic.

Meaning Cloud allows us to easily train an LLM by uploading a spreadsheet with a few tagged keywords.

GPT for Sheets connects Google Sheets with the OpenAI API so we can give prompts like “Which of the following topics would this keyword best fit? Category 1, category 2, category 3, etc.”

LLMs like Chat GPT, Claude, or Gemini have become good enough that you can easily use them to assign topics as well. Just prompt for consistency!

4. Categorize the keywords by intent, and then group or sort your sheet by intent. Check out Query Fan Out to learn why.

5. Don’t build too granular and expansive of a keyword universe that you can’t activate it.

If you have a team of in-house strategists and three part-time freelancers, expecting a 3,000 keyword universe to feel doable and attainable is … an unmet expectation.

Your Keyword Universe Is Designed To Explore

The old way of doing SEO – chasing high-volume keywords and hoping for conversions – isn’t built for today’s search reality.

Trust is hard to earn. (And traffic is hard to come by.)

The keyword universe gives you a living, breathing SEO operating system. One that can evolve based on your custom scoring and prioritization.

Prioritizing what’s important (sorting) allows us to literally filter through the noise (distractions, offers, shiny objects) and bring us to where we want to be.

So, start with your old keyword docs. (Or toss them out if they’re irrelevant, aged poorly, or simply hyper-focused on volume.)

Then, dig into what your customers are really asking. Build smart signals. Assign weights. And refine as you go.

This isn’t about perfection. It’s about building a system that actually works for you.

And speaking of building a system…

Keyword Universe Tracker (For Premium Subscribers)

For premium Growth Memo subscribers, we’ve got a tool that will help save you time and score queries by unique priority weights that you set.

More Resources: 

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Featured Image: Paulo Bobita/Search Engine Journal

https://www.searchenginejournal.com/keywords-are-dead-but-the-keyword-universe-isnt/550188/

Google long ago filed a patent for ranking search results by trust. The groundbreaking idea behind the patent is that user behavior can be used as a starting point for developing a ranking signal.

The big idea behind the patent is that the Internet is full of websites all linking to and commenting about each other. But which sites are trustworthy? Google’s solution is to utilize user behavior to indicate which sites are trusted and then use the linking and content on those sites to reveal more sites that are trustworthy for any given topic.

PageRank is basically the same thing only it begins and ends with one website linking to another website. The innovation of Google’s trust ranking patent is to put the user at the start of that trust chain like this:

User trusts X Websites > X Websites trust Other Sites > This feeds into Google as a ranking signal

The trust originates from the user and flows to trust sites that themselves provide anchor text, lists of other sites and commentary about other sites.

That, in a nutshell, is what Google’s trust-based ranking algorithm is about.

The deeper insight is that it reveals Google’s groundbreaking approach to letting users be a signal of what’s trustworthy. You know how Google keeps saying to create websites for users? This is what the trust patent is all about, putting the user in the front seat of the ranking algorithm.

Google’s Trust And Ranking Patent

The patent was coincidentally filed around the same period that Yahoo and Stanford University published a Trust Rank research paper which is focused on identifying spam pages.

Google’s patent is not about finding spam. It’s focused on doing the opposite, identifying trustworthy web pages that satisfy the user’s intent for a search query.

How Trust Factors Are Used

The first part of any patent consists of an Abstract section that offers a very general description of the invention that that’s what this patent does as well.

The patent abstract asserts:

• That trust factors are used to rank web pages.
• The trust factors are generated from “entities” (which are later described to be the users themselves, experts, expert web pages, and forum members) that link to or comment about other web pages).
• Those trust factors are then used to re-rank web pages.
• Re-ranking web pages kicks in after the normal ranking algorithm has done its thing with links, etc.

Here’s what the Abstract says:

“A search engine system provides search results that are ranked according to a measure of the trust associated with entities that have provided labels for the documents in the search results.

A search engine receives a query and selects documents relevant to the query.

The search engine also determines labels associated with selected documents, and the trust ranks of the entities that provided the labels.

The trust ranks are used to determine trust factors for the respective documents. The trust factors are used to adjust information retrieval scores of the documents. The search results are then ranked based on the adjusted information retrieval scores.”

As you can see, the Abstract does not say who the “entities” are nor does it say what the labels are yet, but it will.

Field Of The Invention

The next part is called the Field Of The Invention. The purpose is to describe the technical domain of the invention (which is information retrieval) and the focus (trust relationships between users) for the purpose of ranking web pages.

Here’s what it says:

“The present invention relates to search engines, and more specifically to search engines that use information indicative of trust relationship between users to rank search results.”

Now we move on to the next section, the Background, which describes the problem this invention solves.

Background Of The Invention

This section describes why search engines fall short of answering user queries (the problem) and why the invention solves the problem.

The main problems described are:

• Search engines are essentially guessing (inference) what the user’s intent is when they only use the search query.
• Users rely on expert-labeled content from trusted sites (called vertical knowledge sites) to tell them which web pages are trustworthy
• Explains why the content labeled as relevant or trustworthy is important but ignored by search engines.
• It’s important to remember that this patent came out before the BERT algorithm and other natural language approaches that are now used to better understand search queries.

This is how the patent explains it:

“An inherent problem in the design of search engines is that the relevance of search results to a particular user depends on factors that are highly dependent on the user’s intent in conducting the search—that is why they are conducting the search—as well as the user’s circumstances, the facts pertaining to the user’s information need.

Thus, given the same query by two different users, a given set of search results can be relevant to one user and irrelevant to another, entirely because of the different intent and information needs.”

Next it goes on to explain that users trust certain websites that provide information about certain topics:

“…In part because of the inability of contemporary search engines to consistently find information that satisfies the user’s information need, and not merely the user’s query terms, users frequently turn to websites that offer additional analysis or understanding of content available on the Internet.”

Websites Are The Entities

The rest of the Background section names forums, review sites, blogs, and news websites as places that users turn to for their information needs, calling them vertical knowledge sites. Vertical Knowledge sites, it’s explained later, can be any kind of website.

The patent explains that trust is why users turn to those sites:

“This degree of trust is valuable to users as a way of evaluating the often bewildering array of information that is available on the Internet.”

To recap, the “Background” section explains that the trust relationships between users and entities like forums, review sites, and blogs can be used to influence the ranking of search results. As we go deeper into the patent we’ll see that the entities are not limited to the above kinds of sites, they can be any kind of site.

Patent Summary Section

This part of the patent is interesting because it brings together all of the concepts into one place, but in a general high-level manner, and throws in some legal paragraphs that explain that the patent can apply to a wider scope than is set out in the patent.

The Summary section appears to have four sections:

• The first section explains that a search engine ranks web pages that are trusted by entities (like forums, news sites, blogs, etc.) and that the system maintains information about these labels about trusted web pages.
• The second section offers a general description of the work of the entities (like forums, news sites, blogs, etc.).
• The third offers a general description of how the system works, beginning with the query, the assorted hand waving that goes on at the search engine with regard to the entity labels, and then the search results.
• The fourth part is a legal explanation that the patent is not limited to the descriptions and that the invention applies to a wider scope. This is important. It enables Google to use a non-existent thing, even something as nutty as a “trust button” that a user selects to identify a site as being trustworthy as an example. This enables an example like a non-existent “trust button” to be a stand-in for something else, like navigational queries or Navboost or anything else that is a signal that a user trusts a website.

Here’s a nutshell explanation of how the system works:

• The user visits sites that they trust and click a “trust button” that tells the search engine that this is a trusted site.
• The trusted site “labels” other sites as trusted for certain topics (the label could be a topic like “symptoms”).
• A user asks a question at a search engine (a query) and uses a label (like “symptoms”).
• The search engine ranks websites according to the usual manner then it looks for sites that users trust and sees if any of those sites have used labels about other sites.
• Google ranks those other sites that have had labels assigned to them by the trusted sites.

Here’s an abbreviated version of the third part of the Summary that gives an idea of the inner workings of the invention:

“A user provides a query to the system…The system retrieves a set of search results… The system determines which query labels are applicable to which of the search result documents. … determines for each document an overall trust factor to apply… adjusts the …retrieval score… and reranks the results.”

Here’s that same section in its entirety:

• “A user provides a query to the system; the query contains at least one query term and optionally includes one or more labels of interest to the user.
• The system retrieves a set of search results comprising documents that are relevant to the query term(s).
• The system determines which query labels are applicable to which of the search result documents.
• The system determines for each document an overall trust factor to apply to the document based on the trust ranks of those entities that provided the labels that match the query labels.
• Applying the trust factor to the document adjusts the document’s information retrieval score, to provide a trust adjusted information retrieval score.
• The system reranks the search result documents based at on the trust adjusted information retrieval scores.”

The above is a general description of the invention.

The next section, called Detailed Description, deep dives into the details. At this point it’s becoming increasingly evident that the patent is highly nuanced and can not be reduced to simple advice similar to: “optimize your site like this to earn trust.”

A large part of the patent hinges on a trust button and an advanced search query:  label:

Neither the trust button or the label advanced search query have ever existed. As you’ll see, they are quite probably stand-ins for techniques that Google doesn’t want to explicitly reveal.

Detailed Description In Four Parts

The details of this patent are located in four sections within the Detailed Description section of the patent. This patent is not as simple as 99% of SEOs say it is.

These are the four sections:

1. System Overview
2. Obtaining and Storing Trust Information
3. Obtaining and Storing Label Information
4. Generated Trust Ranked Search Results

The System Overview is where the patent deep dives into the specifics. The following is an overview to make it easy to understand.

System Overview

1. Explains how the invention (a search engine system) ranks search results based on trust relationships between users and the user-trusted entities who label web content.

2. The patent describes a “trust button” that a user can click that tells Google that a user trusts a website or trusts the website for a specific topic or topics.

3. The patent says a trust related score is assigned to a website when a user clicks a trust button on a website.

4. The trust button information is stored in a trust database that’s referred to as #190.

Here’s what it says about assigning a trust rank score based on the trust button:

“The trust information provided by the users with respect to others is used to determine a trust rank for each user, which is measure of the overall degree of trust that users have in the particular entity.”

Trust Rank Button

The patent refers to the “trust rank” of the user-trusted websites. That trust rank is based on a trust button that a user clicks to indicate that they trust a given website, assigning a trust rank score.

The patent says:

“…the user can click on a “trust button” on a web page belonging to the entity, which causes a corresponding record for a trust relationship to be recorded in the trust database 190.

In general any type of input from the user indicating that such as trust relationship exists can be used.”

The trust button has never existed and the patent quietly acknowledges this by stating that any type of input can be used to indicate the trust relationship.

So what is it? I believe that the “trust button” is a stand-in for user behavior metrics in general, and site visitor data in particular. The patent Claims section does not mention trust buttons at all but does mention user visitor data as an indicator of trust.

Here are several passages that mention site visits as a way to understand if a user trusts a website:

“The system can also examine web visitation patterns of the user and can infer from the web visitation patterns which entities the user trusts. For example, the system can infer that a particular user trust a particular entity when the user visits the entity’s web page with a certain frequency.”

The same thing is stated in the Claims section of the patent, it’s the very first claim they make for the invention:

“A method performed by data processing apparatus, the method comprising:
determining, based on web visitation patterns of a user, one or more trust relationships indicating that the user trusts one or more entities;”

It may very well be that site visitation patterns and other user behaviors are what is meant by the “trust button” references.

Labels Generated By Trusted Sites

The patent defines trusted entities as news sites, blogs, forums, and review sites, but not limited to those kinds of sites, it could be any other kind of website.

Trusted websites create references to other sites and in that reference they label those other sites as being relevant to a particular topic. That label could be an anchor text. But it could be something else.

The patent explicitly mentions anchor text only once:

“In some cases, an entity may simply create a link from its site to a particular item of web content (e.g., a document) and provide a label 107 as the anchor text of the link.”

Although it only explicitly mentions anchor text once, there are other passages where it anchor text is strongly implied, for example, the patent offers a general description of labels as describing or categorizing the content found on another site:

“…labels are words, phrases, markers or other indicia that have been associated with certain web content (pages, sites, documents, media, etc.) by others as descriptive or categorical identifiers.”

Labels And Annotations

Trusted sites link out to web pages with labels and links. The combination of a label and a link is called an annotation.

This is how it’s described:

“An annotation 106 includes a label 107 and a URL pattern associated with the label; the URL pattern can be specific to an individual web page or to any portion of a web site or pages therein.”

Labels Used In Search Queries

Users can also search with “labels” in their queries by using a non-existent “label:” advanced search query. Those kinds of queries are then used to match the labels that a website page is associated with.

This is how it’s explained:

“For example, a query “cancer label:symptoms” includes the query term “cancel” and a query label “symptoms”, and thus is a request for documents relevant to cancer, and that have been labeled as relating to “symptoms.”

Labels such as these can be associated with documents from any entity, whether the entity created the document, or is a third party. The entity that has labeled a document has some degree of trust, as further described below.”

What is that label in the search query? It could simply be certain descriptive keywords, but there aren’t any clues to speculate further than that.

The patent puts it all together like this:

“Using the annotation information and trust information from the trust database 190, the search engine 180 determines a trust factor for each document.”

Takeaway:

A user’s trust is in a website. That user-trusted website is not necessarily the one that’s ranked, it’s the website that’s linking/trusting another relevant web page. The web page that is ranked can be the one that the trusted site has labeled as relevant for a specific topic and it could be a web page in the trusted site itself. The purpose of the user signals is to provide a starting point, so to speak, from which to identify trustworthy sites.

Experts Are Trusted

Vertical Knowledge Sites, sites that users trust, can host the commentary of experts. The expert could be the publisher of the trusted site as well. Experts are important because links from expert sites are used as part of the ranking process.

Experts are defined as publishing a deep level of content on the topic:

“These and other vertical knowledge sites may also host the analysis and comments of experts or others with knowledge, expertise, or a point of view in particular fields, who again can comment on content found on the Internet.

For example, a website operated by a digital camera expert and devoted to digital cameras typically includes product reviews, guidance on how to purchase a digital camera, as well as links to camera manufacturer’s sites, new products announcements, technical articles, additional reviews, or other sources of content.

To assist the user, the expert may include comments on the linked content, such as labeling a particular technical article as “expert level,” or a particular review as “negative professional review,” or a new product announcement as ;new 10MP digital SLR’.”

Links From Expert Sites

Links and annotations from user-trusted expert sites are described as sources of trust information:

“For example, Expert may create an annotation 106 including the label 107 “Professional review” for a review 114 of Canon digital SLR camera on a web site “www.digitalcameraworld.com”, a label 107 of “Jazz music” for a CD 115 on the site “www.jazzworld.com”, a label 107 of “Classic Drama” for the movie 116 “North by Northwest” listed on website “www.movierental.com”, and a label 107 of “Symptoms” for a group of pages describing the symptoms of colon cancer on a website 117 “www.yourhealth.com”.

Note that labels 107 can also include numerical values (not shown), indicating a rating or degree of significance that the entity attaches to the labeled document.

Expert’s web site 105 can also include trust information. More specifically, Expert’s web site 105 can include a trust list 109 of entities whom Expert trusts. This list may be in the form of a list of entity names, the URLs of such entities’ web pages, or by other identifying information. Expert’s web site 105 may also include a vanity list 111 listing entities who trust Expert; again this may be in the form of a list of entity names, URLs, or other identifying information.”

Inferred Trust

The patent describes additional signals that can be used to signal (infer) trust. These are more traditional type signals like links, a list of trusted web pages (maybe a resources page?) and a list of sites that trust the website.

These are the inferred trust signals:

“(1) links from the user’s web page to web pages belonging to trusted entities;
(2) a trust list that identifies entities that the user trusts; or
(3) a vanity list which identifies users who trust the owner of the vanity page.”

Another kind of trust signal that can be inferred is from identifying sites that a user tends to visit.

The patent explains:

“The system can also examine web visitation patterns of the user and can infer from the web visitation patterns which entities the user trusts. For example, the system can infer that a particular user trusts a particular entity when the user visits the entity’s web page with a certain frequency.”

Takeaway:

That’s a pretty big signal and I believe that it suggests that promotional activities that encourage potential site visitors to discover a site and then become loyal site visitors can be helpful. For example, that kind of signal can be tracked with branded search queries. It could be that Google is only looking at site visit information but I think that branded queries are an equally trustworthy signal, especially when those queries are accompanied by labels… ding, ding, ding!

The patent also lists some kind of out there examples of inferred trust like contact/chat list data. It doesn’t say social media, just contact/chat lists.

Trust Can Decay or Increase

Another interesting feature of trust rank is that it can decay or increase over time.

The patent is straightforward about this part:

“Note that trust relationships can change. For example, the system can increase (or decrease) the strength of a trust relationship for a trusted entity. The search engine system 100 can also cause the strength of a trust relationship to decay over time if the trust relationship is not affirmed by the user, for example by visiting the entity’s web site and activating the trust button 112.”

Trust Relationship Editor User Interface

Directly after the above paragraph is a section about enabling users to edit their trust relationships through a user interface. There has never been such a thing, just like the non-existent trust button.

This is possibly a stand-in for something else. Could this trusted sites dashboard be Chrome browser bookmarks or sites that are followed in Discover? This is a matter for speculation.

Here’s what the patent says:

“The search engine system 100 may also expose a user interface to the trust database 190 by which the user can edit the user trust relationships, including adding or removing trust relationships with selected entities.

The trust information in the trust database 190 is also periodically updated by crawling of web sites, including sites of entities with trust information (e.g., trust lists, vanity lists); trust ranks are recomputed based on the updated trust information.”

What Google’s Trust Patent Is About

Google’s Search Result Ranking Based On Trust patent describes a way of leveraging user-behavior signals to understand which sites are trustworthy. The system then identifies sites that are trusted by the user-trusted sites and uses that information as a ranking signal. There is no actual trust rank metric, but there are ranking signals related to what users trust. Those signals can decay or increase based on factors like whether a user still visits those sites.

The larger takeaway is that this patent is an example of how Google is focused on user signals as a ranking source, so that they can feed that back into ranking sites that meet their needs. This means that instead of doing things because “this is what Google likes,” it’s better to go even deeper and do things because users like it. That will feed back to Google through these kinds of algorithms that measure user behavior patterns, something we all know Google uses.

Featured Image by Shutterstock/samsulalam

https://www.searchenginejournal.com/googles-trust-ranking-patent-shows-how-user-behavior-is-a-signal/550203/

Google confirms the June 2025 core update is now rolling out and may take up to three weeks to complete.

• Google’s June 2025 core update began rolling out on June 30.
• It may take up to three weeks to complete.
• Ranking volatility is expected throughout the rollout period.

https://www.searchenginejournal.com/google-rolls-out-june-2025-core-update/550161/

Google announced a new multi-vector retrieval algorithm called MUVERA that speeds up retrieval and ranking, and improves accuracy. The algorithm can be used for search, recommender systems (like YouTube), and for natural language processing (NLP).

Although the announcement did not explicitly say that it is being used in search, the research paper makes it clear that MUVERA enables efficient multi-vector retrieval at web scale, particularly by making it compatible with existing infrastructure (via MIPS) and reducing latency and memory footprint.

Vector Embedding In Search

Vector embedding is a multidimensional representation of the relationships between words, topics and phrases. It enables machines to understand similarity through patterns such as words that appear within the same context or phrases that mean the same things. Words and phrases that are related occupy spaces that are closer to each other.

• The words “King Lear” will be close to the phrase “Shakespeare tragedy.”
• The words “A Midsummer Night’s Dream” will occupy a space close to “Shakespeare comedy.”
• Both “King Lear” and “A Midsummer Night’s Dream” will be located in a space close to Shakespeare.

The distances between words, phrases and concepts (technically a mathematical similarity measure) define how closely related each one is to the other. These patterns enable a machine to infer similarities between them.

MUVERA Solves Inherent Problem Of Multi-Vector Embeddings

The MUVERA research paper states that neural embeddings have been a feature of information retrieval for ten years and cites the ColBERT multi-vector model research paper from 2020 as a breakthrough but that says that it suffers from a bottleneck that makes it less than ideal.

“Recently, beginning with the landmark ColBERT paper, multi-vector models, which produce a set of embedding per data point, have achieved markedly superior performance for IR tasks. Unfortunately, using these models for IR is computationally expensive due to the increased complexity of multi-vector retrieval and scoring.”

Google’s announcement of MUVERA echoes those downsides:

“… recent advances, particularly the introduction of multi-vector models like ColBERT, have demonstrated significantly improved performance in IR tasks. While this multi-vector approach boosts accuracy and enables retrieving more relevant documents, it introduces substantial computational challenges. In particular, the increased number of embeddings and the complexity of multi-vector similarity scoring make retrieval significantly more expensive.”

Could Be A Successor To Google’s RankEmbed Technology?

The United States Department of Justice (DOJ) antitrust lawsuit resulted in testimony that revealed that one of the signals used to create the search engine results pages (SERPs) is called RankEmbed, which was described like this:

“RankEmbed is a dual encoder model that embeds both query and document into embedding space. Embedding space considers semantic properties of query and document in addition to other signals. Retrieval and ranking are then a dot product (distance measure in the embedding space)… Extremely fast; high quality on common queries but can perform poorly for tail queries…”

MUVERA is a technical advancement that addresses the performance and scaling limitations of multi-vector systems, which themselves are a step beyond dual-encoder models (like RankEmbed), providing greater semantic depth and handling of tail query performance.

The breakthrough is a technique called Fixed Dimensional Encoding (FDE), which divides the embedding space into sections and combines the vectors that fall into each section to create a single, fixed-length vector, making it faster to search than comparing multiple vectors. This allows multi-vector models to be used efficiently at scale, improving retrieval speed without sacrificing the accuracy that comes from richer semantic representation.

According to the announcement:

“Unlike single-vector embeddings, multi-vector models represent each data point with a set of embeddings, and leverage more sophisticated similarity functions that can capture richer relationships between datapoints.

While this multi-vector approach boosts accuracy and enables retrieving more relevant documents, it introduces substantial computational challenges. In particular, the increased number of embeddings and the complexity of multi-vector similarity scoring make retrieval significantly more expensive.

In ‘MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings’, we introduce a novel multi-vector retrieval algorithm designed to bridge the efficiency gap between single- and multi-vector retrieval.

…This new approach allows us to leverage the highly-optimized MIPS algorithms to retrieve an initial set of candidates that can then be re-ranked with the exact multi-vector similarity, thereby enabling efficient multi-vector retrieval without sacrificing accuracy.”

Multi-vector models can provide more accurate answers than dual-encoder models but this accuracy comes at the cost of intensive compute demands. MUVERA solves the complexity issues of multi-vector models, thereby creating a way to achieve greater accuracy of multi-vector approaches without the the high computing demands.

What Does This Mean For SEO?

MUVERA shows how modern search ranking increasingly depends on similarity judgments rather than old-fashioned keyword signals that SEO tools and SEOs are often focused on. SEOs and publishers may wish to shift their attention from exact phrase matching toward aligning with the overall context and intent of the query. For example, when someone searches for “corduroy jackets men’s medium,” a system using MUVERA-like retrieval is more likely to rank pages that actually offer those products, not pages that simply mention “corduroy jackets” and include the word “medium” in an attempt to match the query.

Read Google’s announcement:

MUVERA: Making multi-vector retrieval as fast as single-vector search

Featured Image by Shutterstock/bluestork

https://www.searchenginejournal.com/googles-new-muvera-algorithm-improves-search/550070/

The travel and tourism industry thrives on inspiration, discovery, and experience. While increasingly being challenged by social media and friend & family referrals, the first point of discovery for many travelers is still a search engine.

For operators in this competitive sector, ranging from boutique hotels and niche tour providers to vacation rental property owners and managers, as well as local attractions, a commanding online presence isn’t just beneficial – it’s fundamental to survival and growth.

This is where Local SEO emerges as a critical driver, connecting businesses with high-intent travelers actively seeking their next destination or experience.

As the search journey includes more AI-driven results, a sophisticated and adaptive Local SEO strategy is crucial.

This guide will navigate the essentials of Local SEO tailored for travel and tourism, incorporating strategies to thrive in the era of Google’s AI Overviews and other AI search platforms.

We’ll explore established best practices and new frontiers to help you enhance visibility, attract qualified leads, and convert searches into bookings.

Why Local SEO Is Non-Negotiable For Your Travel Business

Today’s travelers are digital nomads even before they pack their bags. They meticulously research, compare, and seek out authentic local experiences, with search engines as their primary guide.

A staggering 87% of consumers used Google to evaluate local businesses in 2022, according to BrightLocal, and this trend is particularly pronounced in the travel sector.

A robust Local SEO strategy ensures your offerings are prominent when potential customers conduct geographically specific searches. Consider these compelling reasons:

Hyper-Targeted Visibility

Local SEO puts your business in front of users searching for “boutique hotels in downtown Austin” or “eco-tours near me,” connecting you with an audience demonstrating clear local intent.

Increased Organic Traffic & Direct Bookings

Higher visibility in local search translates to more qualified traffic to your website, reducing reliance on commission-heavy Online Travel Agencies (OTAs).

Enhanced Credibility And Trust

Businesses appearing in top local search results, especially those with strong reviews, are perceived as more trustworthy. Indeed, according to Expedia group, studies show that 95% of travelers read reviews before booking

Competitive Edge

In a crowded marketplace, a sophisticated Local SEO strategy will differentiate your unique local offerings from larger, and perhaps less localized competitors.

Cost-Effectiveness

Compared to paid advertising, organic Local SEO can deliver a higher return on investment (ROI) over the long term by building sustainable visibility.

Building A Future-Proof Local SEO Strategy For Travel

To maximize visibility and capture the attention of modern travelers, operators must build their SEO strategy on several key pillars:

An Optimized Google Business Profile (GBP)

For businesses with a physical presence or those catering to broader service areas, a Google Business Profile is arguably the most potent Local SEO tool currently available.

It’s often the first interaction a potential customer has with a brand online, as Google Maps appears at the top of most local searches.

Here are the key GBP best practices you need to implement to leverage this important channel.

• NAP Optimization: Claim and thoroughly complete your GBP listing. Ensure the accuracy of your business Name, Address (or service area), Phone number (NAP), website, hours, and a compelling, keyword-rich description.
• Precise Categorization: Select the most accurate primary and secondary categories truly reflecting your business’s services, e.g., “Boutique Hotel,” “Adventure Tour Operator,” “Vacation Rental Agency.”
• Service Area Definition: For businesses without a fixed customer-facing location (like tour operators) or those serving a broader region, accurately define your service areas. Google advises that this shouldn’t exceed a 2-hour drive from your base. If you serve an area beyond this 2-hour range, you will need to find ways to convince Google via reviews from customers located in the broader area, local partnerships, or perhaps establishing an actual satellite location.
• Visual Storytelling: Invest in and share professional, high-resolution photos and videos of your business, properties, tours, amenities, local ambiance, guest experiences, team, etc.
• Active Engagement via GBP Posts: Regularly use GBP posts to share updates, special offers, upcoming events, new blog content, and local insights. This signals to Google that your business is active and engaged in your community.
• Review Management: Ask for and monitor customer reviews on GBP. Respond promptly and professionally to all reviews. This not only impacts rankings, but can also heavily influence booking decisions – 76% of consumers would update their negative review to a neutral or positive if a company acknowledged and fixed the complaint. Larger organizations with review volume across multiple locations will want to consider centralized and automated review management solutions such as BirdEye or BrightLocal.
• Proactive Q&A Management: Monitor and answer questions in the GBP Q&A section to provide valuable information and manage customer perceptions.

Maintain A High-Performance, Locally Optimized Website

Your website is your digital flagship, where inspiration meets transaction.

Websites remain a core focus for all businesses because they are still the place where primary product and service content is housed, as well as for travel businesses where bookings begin, even if they are ultimately completed off-site.

Several components are involved in optimizing a site for local search.

Strategic Keyword Research

Identify terms your target audience uses at each stage of the travel planning funnel, and particularly those used during the Engage and Booking stages.

Focus on location-specific queries (“luxury safari tours Kenya”), property types (“beachfront villas Maui”), and unique selling propositions (“pet-friendly cabins in the Blue Ridge Mountains”).

On-Page Optimization

Craft unique, keyword-rich Title tags, hierarchical heading structures, and internal/external links for every key bottom-of-the-funnel page.

Review keyword rank, search volume, organic search traffic, and conversion data to determine the primary pages to focus on.

Larger organizations will want to take a broader, scalable approach with page templates, but will still hone attention and focus on key locations where some level of authority and visibility has already been established, upon which momentum can be built.

Dedicated Location/Service Pages

If you cater to multiple distinct areas or offer specialized tours/services per location, create unique, detailed landing pages for each location.

These pages should include unique localized content (particularly if services or products differ by location), local team information, testimonials, contact details, and embedded Google Maps.

Image & Video Optimization

Use descriptive filenames and alt text for all visuals, incorporating relevant keywords and location data, where applicable.

Optimize image file sizes for fast loading (the WebP format is recommended) without compromising quality. This is admittedly a challenge for many in the travel space as images and video can make or break a property, tour, or experience listing.

Mobile-Friendly Design

With a significant portion of travel searches and bookings occurring on mobile (mobile devices made up 70.5% of global online travel traffic in 2024), a responsive, fast-loading website is critical.

Furthermore, site speed is a recognized ranking factor, for which tools like Google PageSpeed Insights and Core Web Vitals are available to gauge and diagnose potential bottlenecks.

Rich, Informative Content

Develop content marketing plans to address traveler questions and showcase your local expertise via detailed itineraries, destination guides, “things to do” lists, and booking information.

Structured Data (Schema Markup)

Implement relevant schema, such as:

• LocalBusiness.
• Hotel.
• LodgingBusiness.
• VacationRental.
• TouristAttraction.
• TouristTrip (for itineraries).
• Event.
• FAQPage.
• Article.

Schema helps search engines (and AI models) understand your content contextually.

Relevant, comprehensive structured data will improve your content’s eligibility for rich snippets and AI Overviews in Google, which are showing up in organic search results with increasing regularity across travel and all industries.

User Experience (UX) And Accessibility

A seamless UX with intuitive navigation, clear calls-to-action, and an easy booking process directly impacts conversion rates.

Further, ensuring your website is accessible to people with disabilities (based on WCAG Guidelines) broadens your target audience and is widely considered SEO best practice.

Building Authority With Off-Page SEO And Reputation Management

Off-page signals from relevant local and/or industry-specific sources significantly influence your local ranking and perceived trustworthiness.

Brand mentions, whether linked or not, are being recognized as an important factor in AI Search visibility.

Businesses looking to boost their local visibility need to consider their broad web presence, in addition to the content they control on their website and GBP.

• NAP Consistency & Local Citations: Ensure your Name, Address, and Phone number (NAP) are identical across all online directories (e.g., Yelp, TripAdvisor, local tourism sites). Inconsistent NAP can harm rankings. Larger operators with multiple locations will want to consider implementing a centralized Listings Management tool like SOCi or Yext.
• Strategic Link Building: Earn and obtain high-quality backlinks from relevant local organizations (tourism boards, chambers of commerce), travel blogs, local press, and complementary businesses.
• Local Partnerships & Community Engagement: Collaborate with nearby businesses (restaurants, activity providers, event organizers) for cross-promotion and local link opportunities. Sponsoring and/or physically participating in local events can also help build visibility and relevant local links.
• Local Influencer Collaboration: Partner with local travel and lifestyle influencers to tap into their engaged audiences with relevant content and messaging, thereby gaining authentic, local endorsements. These types of collaborations generally take time to establish and build trust, but can reap significant benefits by tapping into a loyal, local customer base.

Content Marketing: The Engine Of Local SEO And AI Visibility

High-quality, relevant content is fuel for both visibility in traditional organic and AI-driven search.

• Audience-Centric Content Strategy: Understand your ideal traveler and their journey. Create content that inspires, informs, and facilitates booking.
• Hyperlocal & Unique Storytelling: Develop blog posts, guides, videos, and itineraries highlighting your unique offerings and deep knowledge of the local area. Focus on what makes your experience or destination special, sharing authentic stories and insider tips.
• Answer Questions Directly: Create content, including dedicated FAQ sections, and directly answer common traveler queries. Incorporate a Question and Answer schema to clearly call out this content for search and LLM crawlers. This is vital for appearing in Google’s AI Overviews and being useful to other AI chatbots.
• Diverse Content Formats: Utilize blog articles, high-resolution photo galleries, engaging videos (destination spotlights, property tours, guest testimonials), interactive maps, and downloadable guides. Short-form video is highly effective on social media.
• Content Promotion: Share your content strategically via GBP, social media, email marketing, and local partnerships to maximize its reach and opportunity to be shared further.

Thriving In The Era Of AI Overviews And AI Search

We can’t have an SEO conversation today, Local or otherwise, without considering the impact of AI on search.

Google’s AI Overviews and other AI tools like Perplexity and ChatGPT are changing how users find information.

In a recent Whitespark study, it was determined that AI Overviews are appearing for a significant 68% of local business-type searches.

To optimize for this new paradigm at a local level, there are a few things to consider, some of which you’ll note are in line with the SEO recommendations made above:

• Prioritize E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness): AI models, especially Google’s, are designed to prioritize information from sources that demonstrate the four qualities of E-E-A-T. Ensure your content is accurate, well-researched, or proprietary, written by experts (or showcases expertise), and your website projects credibility.
• Create Comprehensive, Factual, and Well-Structured Content: AI loves well-organized information. Use clear headings, bullet points, and ensure your content thoroughly covers a topic, directly answering common questions. This makes it easier for AI to parse and use your information for generating and displaying summaries.
• Optimize for Conversational & Question-Based Queries: Think about how users ask questions about your business, products, or services verbally or in natural language. Structure content around these queries (e.g., “What are the best family-friendly hotels in Orlando with a water park?”).
• Reinforce Entity Recognition: Ensure clear and consistent information about your business (your “entity”) across the web – your name, what you do, where you’re located, and unique offerings.
• Structured Data Matters Even More: As mentioned, schema markup helps search engines and AI Large Language Models (LLMs) understand the specifics of your content (business, products, etc), thereby improving its ability to be accurately represented in AI-generated results.
• Ensure Broad Web Presence and Citations: AI models like Perplexity cite their sources. Being mentioned and linked to from other authoritative travel sites, blogs, and news outlets can increase your chances of being referenced.
• Monitor Your Appearance in AI Search: While direct tracking in AI Overviews and other AI search platforms is still in development, consider leveraging new third-party tools and conducting manual checks to determine if and how your business or content is appearing in AI-generated responses for relevant queries.

Track, Analyze, And Adapt

Any worthwhile and effective Local SEO effort is backed by data.

Use Google Analytics, Google Search Console, and other SEO tools to monitor key metrics, including organic traffic, keyword rankings (especially local), Google Business Profile insights (views, clicks, calls, direction requests), conversion rates, and referral traffic from local sources.

This data will be key to helping you continually refine your strategy as modern SEO (and now GEO or AEO) is a moving target.

The Future Is Local And AI-Enhanced

Local SEO is no longer a niche tactic, but a foundational element of a successful digital marketing strategy for any travel and tourism operator.

By focusing on providing genuine value to travelers, creating exceptional local experiences, and meticulously optimizing your online presence across all relevant platforms, you can attract more customers.

As AI continues to reshape search, the emphasis on high quality, authoritative, and clearly structured content, along with a broad-based, brand-forward web presence, becomes even more important.

Embrace the principles and tactics here, stay agile, and you’ll be well-positioned to navigate the evolving digital landscape and welcome more guests through your virtual and physical doors.

More resources:

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Featured Image: RobinRmD/Shutterstock

https://www.searchenginejournal.com/mastering-local-seo-strategic-imperative-travel-and-tourism-operators/547350/

Google is testing a new feature that allows you to customize the Top Stories section in search results by selecting preferred news sources.

Currently available through Search Labs in the U.S. and India, the experiment gives people more influence over which publishers appear in their news-related queries.

How It Works

Those who opt into the experiment will see a new starred icon in the Top Stories carousel. Tapping it opens a menu where you can choose preferred publications.

Articles from selected sources will be more likely to appear in Top Stories when relevant. These entries will be marked with a star icon next to the site name, but they won’t replace Google’s algorithmic selections entirely.

Google may also display a secondary “From your sources” carousel beneath the main Top Stories section.

A Broader Shift Toward Personalization

The Preferred Sources feature builds on Google’s existing personalization tools, including the ability to highlight content users have frequently visited or show updates since their last search.

A “Try without personalization” option remains available at the bottom of search results, maintaining transparency and user control.

What This Means

For publishers, this change could offer increased visibility, especially for those with loyal audiences who choose them as preferred sources.

However, smaller or newer outlets may struggle to compete with established brands if user selections skew toward familiar names.

The experiment highlights the growing importance of brand recognition, direct audience relationships, and consistent content freshness.

Looking Ahead

This initiative is part of Google’s effort to balance algorithmic discovery with user-driven customization.

While it’s still an experiment, the move suggests Google is exploring ways to give users more say in how information surfaces, without fully abandoning its ranking systems.

If rolled out more broadly, the Preferred Sources feature could reshape strategies for publishers and marketers seeking consistent visibility in Google Search.

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Featured Image: Roman Samborskyi/Shutterstock

https://www.searchenginejournal.com/google-tests-preferred-sources-to-personalize-top-stories-in-search/550037/

Google’s transformation into an AI-driven search platform represents more than just a technological advancement. It’s a fundamental shift in how the search giant views itself as a company and the value it provides to users.

Cindy Krum has spoken at several events this year about her theory that Google might merge AI Overviews, Discover, and international results to build the next-gen search engine.

The overview of Cindy’s thoughts is that Google is not only internationalizing its platform, but is also converging AI Overview, Google Discover, and AI Mode into a unified, hyper-personalized search experience.

This evolution aligns with Google’s broader push toward understanding search as “journeys” rather than static queries, underlined by MUM.

My theory is that the move into heavily personalized search journeys builds on the past 20 years that Google has been striving to be a personal assistant. AI has made that possible.

Cindy is the founder of MobileMoxie and is described as being “years ahead of the pack.” I spoke to her about the implications for SEO and what part of this shift to AI-organized search and journeys SEO professionals are underestimating right now.

You can watch the full interview with Cindy on IMHO below, or continue reading the article summary.

[embedded content]

Predictive, Conversational, And Personalized

Cindy believes that, currently, there is a bigger shift than what some SEO professionals have been talking about: A fundamental shift in the way Google sees itself as a company and the way that it sees the value that it provides.

The real shift was in 2018, just after Google launched mobile-first indexing, when Google began organizing search results around entities. It said it wanted to be more predictive, more conversational, and more personalized.

According to Cindy, Google’s current AI initiatives aren’t new developments but rather the culmination of a strategy.

“Everything they’ve been doing since 2018 has been feeding this goal of getting us into this AI search reality,” she explains.

The AI Overviews, Google Discover expansion, and AI Mode we see today are direct results of this seven-year journey.

The Hidden Strategy Behind Google’s International Push

One of the most overlooked aspects of Google’s current transformation is its renewed attempt to consolidate international domains.

Google previously tried to eliminate country-specific versions (CCTLDs) before mobile-first indexing but had to roll back the initiative. Now, it is trying again, and the timing is significant.

“If you separate everything by country and language, you’re limiting your learning pipeline. You have smaller, fragmented datasets.” Cindy explains.

When you consolidate and abstract at the entity level, you can disambiguate meaning and link keywords to entity ideas across all languages. That speeds up the learning process.

Google can then apply what it learns in one language to another; we’re already seeing this with AI Overviews.

When it can’t find the right answer in a local language, it translates English content because it knows the English answer is probably also correct in other languages. This saves time and money on crawling, indexing, and ranking.

AI Mode Isn’t The Product. You Are

I asked Cindy if she thought Google might try to monetize AI Mode, but she believes Google’s strategy is more sophisticated.

“We can’t forget how Google makes money, it’s ads,” Cindy emphasizes. The real value lies in building comprehensive user profiles that enable precision ad targeting.

Google’s goal is to present ads only to users likely to convert, making its advertising platform more attractive to businesses while creating a seamless experience for users.

“They’re not monetizing AI Mode directly. They’re using it to collect data that allows them to monetize ads more effectively.”

This strategy extends to Performance Max campaigns on the paid search side, where Google controls optimization based on metrics it doesn’t trust advertisers to manage effectively.

Discovery Is Moving To TikTok, Reddit & Social

Despite Google’s technological advances, some users are losing trust in the quality of search results.

However, the solution isn’t abandoning Google but rather understanding how different platforms serve different purposes in the modern search ecosystem.

Cindy’s opinion is that Google is no longer the place where discovery happens.

Users increasingly conduct research across multiple platforms. TikTok for discovery, Reddit for authentic opinions, and eventually Google for final purchase decisions.

This multi-platform journey reflects a more sophisticated approach to information gathering and decision-making.

Cindy stresses the need to understand real branding, not just SEO branding or digital PR.

“To be able to influence the narrative in any kind of AI search result, you have to be actively influencing all those things,” she notes. “SEOs for years have been so focused on their website to the detriment of every other branding opportunity out there.”

Understanding Search Journeys

For SEO professionals looking to optimize for journeys rather than just keywords, Cindy recommends studying Google’s own navigation suggestions.

When performing searches, Google often displays additional navigation layers that reveal its understanding of user intent and likely next steps.

“This is where Google is kind of showing their cards and saying these are the queries that we expect you’re going to narrow down this query,” she explains.

By mapping these suggested pathways, SEO professionals can identify where their content fits into the user journey and where Google needs education about additional aspects of that journey.

If She Were Starting Today? TikTok

I asked Cindy if she were starting from the beginning now, what she would do and where she would invest, her immediate answer was TikTok.

She explains, “It’s where young audiences are, the algorithm promotes discovery, and content is repurposed across all other platforms. Importantly, it’s not just a fad; businesses are being built and scaled directly on TikTok.”

And while influencer saturation is real, Cindy sees TikTok as a smart, scrappy way to build awareness with a small budget and scale fast.

Preparing For The Future

The shift toward AI-organized search results and journey-based optimization requires a fundamental rethinking of digital marketing approaches.

Success in this new era of AI search demands understanding the complete customer journey, from initial discovery through final purchase, and ensuring brand presence at every touchpoint.

This includes active participation in the broader digital conversation about your industry, products, and services.

The future of search isn’t just about ranking higher; it’s about being present wherever your audience might encounter your brand throughout their decision-making journey.

“The future of search is understanding the entire journey, not just the keyword or the query.”

Thank you to Cindy Krum for offering her insights and being my guest on IMHO.

More Resources:

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Featured Image: Shelley Walsh/Search Engine Journal

https://www.searchenginejournal.com/googles-ai-search-journeys-are-reshaping-seo-with-cindy-krum/549614/

This post was sponsored by InMotion Hosting. The opinions expressed in this article are the sponsor’s own.

We’ve all felt it, that sinking feeling in your stomach when your site starts crawling instead of sprinting.

Page speed reports start flashing red. Search Console is flooding your inbox with errors.

You know it’s time for better hosting, but here’s the thing: moving a large website without tanking your SEO is like trying to change tires while your car is still moving.

We’ve seen too many migrations go sideways, which is why we put together this guide.

Let’s walk through a migration plan that works. One that’ll future-proof your site without disrupting your rankings or overburdening your team.

Step 1: Set Your Performance Goals & Audit Your Environment

Establish Performance Benchmarks

Before you touch a single line of code, you need benchmarks. Think of these as your “before” pictures in a website makeover.

If you skip this step, you’ll regret it later. How will you know if your migration was successful if you don’t know where you started?

Gather your current page speed numbers, uptime percentages, and server response times. These will serve as proof that the migration was worth it.

Document Current Site Architecture

Next, let’s identify what’s working for your site and what’s holding it back. Keep a detailed record of your current setup, including your content management system (CMS), plugins, traffic patterns, and peak periods.

Large sites often have unusual, hidden connections that only reveal themselves at the worst possible moments during migrations. Trust us, documenting this now prevents those 2 AM panic attacks later.

Define Your Website Migration Goals

Let’s get specific about what success looks like. Saying “we want the site to be faster” is like saying “we want more leads.” It sounds great, but how do you measure it?

Aim for concrete targets, such as:

• Load times under 2 seconds on key pages (we like to focus on product pages first).
• 99.99% uptime guarantees (because every minute of downtime is money down the drain).
• Server response times under 200ms.
• 30% better crawl efficiency (so Google sees your content updates).

We recommend running tests with Google Lighthouse and GTmetrix at different times of day. You’d be surprised how performance can vary between your morning coffee and afternoon slump.

Your top money-making pages deserve special attention during migration, so keep tabs on those.

Step 2: Choose The Right Hosting Fit

Not all hosting options can handle the big leagues.

We’ve seen too many migrations fail because someone picked a hosting plan better suited for a personal blog than an enterprise website.

Match Your Needs To Solutions

Let’s break down what we’ve found works best.

Managed VPS is excellent for medium-sized sites. If you’re receiving 100,000 to 500,000 monthly visitors, this might be your sweet spot. You’ll have the control you need without the overkill.

Dedicated servers are what we recommend for the major players. If you’re handling millions of visitors or running complex applications, this is for you.

What we appreciate about dedicated resources is that they eliminate the “noisy neighbor” problem, where someone else’s traffic spike can tank your performance. Enterprise sites on dedicated servers load 40-60% faster and rarely experience those resource-related outages.

WordPress-optimized hosting is ideal if you’re running WordPress. These environments come pre-tuned with built-in caching and auto-updates. Why reinvent the wheel, right?

Understand The Must-Have Features Checklist

Let’s talk about what your web hosting will need for SEO success.

NVMe SSDs are non-negotiable these days. They’re about six times faster than regular storage for database work, and you’ll feel the difference immediately.

A good CDN is essential if you want visitors from different regions to have the same snappy experience. Server-level caching makes a huge difference, as it reduces processing work and speeds up repeat visits and search crawls.

Staging environments aren’t optional for big migrations. They’re your safety net. Keep in mind that emergency fixes can cost significantly more than setting up staging beforehand.

And please ensure you have 24/7 migration support from actual humans. Not chatbots, real engineers who answer the phone when things go sideways at midnight.

Key Considerations for Growth

Think about where your site is headed, not just where it is now.

Are you launching in new markets? Planning a big PR push? Your hosting should handle growth without making you migrate again six months later.

One thing that often gets overlooked: redirect limits. Many platforms cap at 50,000-100,000 redirects, which sounds like a lot until you’re migrating a massive product catalog.

Step 3: Prep for Migration – The Critical Steps

Preparation separates smooth migrations from disasters. This phase makes or breaks your project.

Build Your Backup Strategy

First things first: backups, backups, backups. We’re talking complete copies of both files and databases.

Don’t dump everything into one giant folder labeled “Site Stuff.” Organizing backups by date and type. Include the entire file system, database exports, configuration files, SSL certificates, and everything else.

Here’s a common mistake we often see: not testing the restore process before migration day. A backup you can’t restore is wasted server space. Always conduct a test restore on a separate server to ensure everything works as expected.

Set Up the New Environment and Test in Staging

Your new hosting environment should closely mirror your production environment. Match PHP versions, database settings, security rules, everything. This isn’t the time to upgrade seven different things at once (we’ve seen that mistake before).

Run thorough pre-launch tests on staging. Check site speed on different page types. Pull out your phone and verify that the mobile display works.

Use Google’s testing tools to confirm that your structured data remains intact. The goal is no surprises on launch day.

Map Out DNS Cutover and Minimize TTL for a Quick Switch

DNS strategy might sound boring, but it can make or break your downtime window.

Here’s what works: reduce your TTL to at least 300 seconds (5 minutes) about 48 hours before migration. This makes DNS changes propagate quickly when you flip the switch.

Have all your DNS records prepared in advance: A records, CNAMEs for subdomains, MX records for email, and TXT records for verification. Keep a checklist and highlight the mission-critical ones that would cause panic if forgotten.

Freeze Non-Essential Site Updates Before Migration

This might be controversial, but we’re advocates for freezing all content and development changes for at least 48 hours before migration.

The last thing you need is someone publishing a new blog post right as you’re moving servers.

You can use this freeze time for team education. It’s a perfect moment to run workshops on technical SEO or explain how site speed affects rankings. Turn downtime into learning time.

Step 4: Go-Live Without the Guesswork

Migration day! This is where all your planning pays off, or where you realize what you forgot.

Launch Timing Is Everything

Choose your timing carefully. You should aim for when traffic is typically lowest.

For global sites, consider the “follow-the-sun” approach. This means migrating region by region during their lowest traffic hours. While it takes longer, it dramatically reduces risk.

Coordinate Your Teams

Clear communication is everything. Everyone should know exactly what they’re doing and when.

Define clear go/no-go decision points. Who makes the call if something looks off? What’s the threshold for rolling back vs. pushing through?

Having these conversations before you’re in the middle of a migration saves a ton of stress.

Live Performance Monitoring

Once you flip the switch, monitoring becomes your best friend. Here are the key items to monitor:

• Watch site speed across different page types and locations.
• Set up email alerts for crawl errors in Search Console.
• Monitor 404 error rates and redirect performance.

Sudden spikes in 404 errors or drops in speed need immediate attention. They’re usually signs that something didn’t migrate correctly.

The faster you catch these issues, the less impact they’ll have on your rankings.

Post-Migration Validation

After launch, run through a systematic checklist:

• Test redirect chains (we recommend Screaming Frog for this).
• Make sure internal links work.
• Verify your analytics tracking (you’d be surprised how often this breaks).
• Check conversion tracking.
• Validate SSL certificates.
• Watch server logs for crawl issues.

One step people often forget: resubmitting your sitemap in Search Console as soon as possible. This helps Google discover your new setup faster.

Even with a perfect migration, most large sites take 3-6 months for complete re-indexing, so patience is key.

Step 5: Optimize, Tune, and Report: How To Increase Wins

The migration itself is just the beginning. Post-migration tuning is where the magic happens.

Fine-Tune Your Configuration

Now that you’re observing real traffic patterns, you can optimize your setup.

Start by enhancing caching rules based on actual user behavior. Adjust compression settings, and optimize those database queries that seemed fine during testing but are sluggish in production.

Handling redirects at the server level, rather than through plugins or CMS settings, is faster and reduces server load.

Automate Performance Monitoring

Set up alerts for issues before they become problems. We recommend monitoring:

• Page speed drops by over 10%.
• Uptime drops.
• Changes in crawl rates.
• Spikes in server resource usage.
• Organic traffic drops by over 20%.

Automation saves you from constantly checking dashboards, allowing you to focus on improvements instead of firefighting.

Analyze for SEO Efficiency

Server logs tell you a lot about how well your migration went from an SEO perspective. Look for fewer crawl errors, faster Googlebot response times, and better crawl budget usage.

Improvements in crawl efficiency mean Google can discover and index your new content much faster.

Measure and Report Success

Compare your post-migration performance to those baseline metrics you wisely collected.

When showing results to executives, connect each improvement to business outcomes. For example:

• “Faster pages reduced our bounce rate by 15%, which means more people are staying on the site.”
• “Better uptime means we’re not losing sales during peak hours.”
• “Improved crawl efficiency means our new products get indexed faster.”

Pro tip: Build easy-to-read dashboards that executives can access at any time. This helps build confidence and alleviate concerns.

Ready to Execute Your High-Performance Migration?

You don’t need more proof that hosting matters. Every slow page load and server hiccup already demonstrates it. What you need is a plan that safeguards your SEO investment while achieving tangible improvements.

This guide provides you with that playbook. You now know how to benchmark, choose the right solutions, and optimize for success.

This approach can be applied to sites of all sizes, ranging from emerging e-commerce stores to large enterprise platforms. The key lies in preparation and partnering with the right support team.

If you’re ready to take action, consider collaborating with a hosting provider that understands the complexities of large-scale migrations. Look for a team that manages substantial redirect volumes and builds infrastructure specifically for high-traffic websites. Your future rankings will thank you!

Image Credits

Featured Image: Image by InMotion Hosting. Used with permission.

In-Post Image: Images by InMotion Hosting. Used with permission.

https://www.searchenginejournal.com/seo-guide-site-migration-inmotionhosting-spa/549001/

Jill Whalen, a true SEO pioneer, recently passed away. Although she has been retired for over ten years, her influence continues in the content-first SEO practices she advocated that are gradually gaining ground thirty years after she first championed that approach to ranking websites.

Contributions To SEO

As part of the first wave of SEO, her contribution to search marketing was to prove that a content-focused approach was sustainable as a long-term strategy. While that style of SEO is described as white hat, that term has lost meaning as many of the SEOs with the biggest and whitest hats tended to be algorithm chasers jumping from strategy to strategy, something Whalen was not.

Many of the second-wave SEOs from my generation focused on testing the limits of search engine algorithms and reading research papers to better understand how search engines worked. Whalen remained steadily focused on creating the kind of content search engines were trying to rank and used responsible link building to promote it, which turned out to be a winning strategy.

Screenshot Of Jill Whalen On SEO Pioneers Show

Her approach may have felt old-fashioned to some in the industry at the time, but she recently observed in an interview on Shelley Walsh’s SEO Pioneers show that she felt vindicated after Google’s Panda and Penguin algorithms, which rocked the search marketing industry but left her clients’ top-ranked websites untouched. Indeed, the entire SEO industry is coming around to Jill’s approach to SEO.

Whalen retired in 2013 and turned her attention to subjects that mattered to her, but her influence has always been felt through the thousands of SEOs who learned from her and who continue to pass those traditions on.

How Jill Whalen Influenced Top SEOs

Christine Churchill

Christine Churchill (LinkedIn profile), a leading search marketer, explains how she met Jill Whalen and how she influenced her life and career.

“Wow, this loss really stings! I first met Jill at a speakers’ gathering that I almost skipped because I was dreading feeling out of place. I told myself to just go for five minutes, and when I walked in, I spotted Jill right away – the only other woman there. She flashed me a warm smile, and I found my way over to the bar where she was sitting. I was so nervous, but I was completely taken aback when she mentioned she had seen me speak at an earlier conference and actually knew who I was!

We ended up chatting until the bar closed, and from that night on, we bonded instantly. Jill had this incredible gift of helping us believe in ourselves and encouraging us to shine. Because of her, I also met amazing people like Debra Mastaler, Scottie Claibourne, Karon Thackston, Kim Krause Berg and so many more kindred spirits. We all became friendly faces in the crowd, supporting each other in countless ways.

Jill truly changed my life, and I got to travel the world alongside her! Even when she retired and we didn’t see each other as much, I always knew that if I needed a friend, she’d be just a call away.

I still remember that one conference (I think it was in Pennsylvania) where we met this fascinating guy who talked to ghosts. We ended up staying at the bar yet again, discussing spirits and the signs our departed loved ones send us. It feels like Jill is with all of us now, saying goodbye and cheering us on to keep blooming.

Thank you, Jill, for your incredible friendship and support. I’ll cherish my memories of you forever!”

Debra Mastaler

My good friend Debra Mastaler (LinkedIn profile) was one of Whalen’s early collaborators, handling link building. Debra shares how Jill was instrumental in shaping her career in SEO:

“I’ve been involved with the SEO industry since 1999, I started by owning a directory of organic food and clothing. When I started to rank well for a large number of money terms, business owners advertising in my directory asked if I could I help them “optimize” their sites. I had no clue what that meant so I started looking around for information and met Jill.

Jill took the time to explain what I was doing was called link building and how important it was. One thing led to another and she hired me to do all her link work and got me on the speaking circuit. About a year later, I felt confident enough to work on my own and I launched Alliance-Link.

Over the years, we traveled together, went to conferences, ran an SEO forum, published content together, shared family vacations and spoke almost every day. We drifted after she left the SEO industry but her mark on my life has never faded.”

Michael Bonfils

Multilingual International SEO Michael Bonfils (LinkedIn profile), also an SEO pioneer himself, nce before SEO described who she was and how she influenced him.

“Twenty five years ago while attending one of the first SES (Search Engine Strategies) conferences in San Francisco, I noticed this incredibly enthusiastic lady who was leading a roundtable discussion about content. There were three things that struck me that I never forget.

• First, she was one of the few women in a sea of nerdy dudes but as nerdy as she was, she fit perfectly in with everyone else.
• Second, she was nervous about speaking, she didn’t say it, but I can see it. I could feel it. It made me happy to know that I wasn’t alone and it was that nervousness that drew me to be one of the first few that sat around her roundtable.
• Third, she explained the power of content in SEO better than anyone else. While everyone was focused on tricking the search engines, she was focused on feeding the search engines exactly what they wanted (I was working for a search engine at the time, so this was important for me to hear.)

From the beginning of her career, I’ve had so much respect for Jill that her and I over the decades would often talk about the good old days when everyone and everything in SEO was so uncertain. When she retired, I told her how bummed I was and then I of course accused her of faking it.

I am really going to miss Jill and just broken hearted to learn of her passing. She was truly a legend.”

Duane Forrester

Duane Forrester (LinkedIn profile, formerly of Bing) described how Jill Whalen helped him understand how to explain complex ideas in ways that were understandable to a wide audience.

“Yeah, safe to say that Jill influenced my sense of direction. I mean, I knew it was about working for/with the algorithms, but there had to be a balance. Not just in terms of the work, but how we explained it. Jill helped set me, personally, on a path of trying to explain the complex in ways that everyday business people could understand and adapt to.

Jill was adept at looking through the complex and finding ways forward that not only worked, but were approachable by a wide variety of people with various skills and skill levels. She had a sharp mind and managed to recall volumes of relevant information seemingly effortlessly.

It was always a highlight of any conference to cross paths with Jill. We lost a treasure and I, and I’m sure many, will miss her.”

Bill Hartzer

Bill Hartzer (LinkedIn profile), one of the sharpest technical SEOs I know, remembered her as a centering voice, one who brought balance back to SEO.

He shared:

“She definitely was an influence, as she was more the “voice of reason” so to speak, when I was always trying to test the limits, test that “fine line” between white hat SEO and gray hat SEO.

She consistently advocated for doing SEO “the right way,” which is with integrity, transparency, and a focus on long-term value. Her work through High Rankings became a trusted symbol of ethical search marketing, long before it became the norm.”

Brett Tabke

Brett Tabke (LinkedIn profile), one of the leading founders of modern SEO, remembered her as a positive influence.

“She was always so nice. Had a smile on her face 90% of the time you were with her. I can’t remember a time when she didn’t appear happy to be with her friends. Even when she was presenting, she always made you feel good about what we were doing.”

Watch The SEO Pioneers Interview With Jill Whalen

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Featured Image/Screenshot from SEO Pioneers interview

https://www.searchenginejournal.com/jill-whalens-seo-legacy-still-shapes-the-industry/549719/

Yoast SEO rushed out an update to fix a bug that introduced a known fingerprint of AI-generated content. The bug was highlighted on social media, and Yoast corrected the error within hours.

HTML Classes Injected By Copy-Pasting

Copying a block of text from a live web page or even a Microsoft Word document and then pasting it into a WordPress editor will also paste the underlying formatting from the original document. That’s basically the reason why copy-pasting content directly from ChatGPT and into a WordPress editor will also inject HTML “classes” code from an AI chatbot output.

An HTML “class” is something that’s added to an HTML element like a paragraph element <p>, which can then be used to attach a style to it, like specifying a font. This bug only happens when a ChatGPT user highlights generated text, copies it, then pastes it into the WordPress editor. It won’t happen if the user clicks the ChatGPT “copy” icon to copy the generated content.

The HTML classes injected into content are “data-start” and “data-end” which are only visible within the code, not on the published content.

This is what AI-generated content looks like with injected classes:

“He thought no one would notice—<br data-start=”31″ data-end=”34″ />the quiet hum of the AI<br data-start=”57″ data-end=”60″ />churning out words<br data-start=”78″ data-end=”81″ />like it knew something.<br data-start=”104″ data-end=”107″ />Google noticed.<br data-start=”122″ data-end=”125″ />Now he shelves canned beans at Safeway.”

This is what the content would look like in the visible version:

“He thought no one would notice—
the quiet hum of the AI
churning out words
like it knew something.
Google noticed.
Now he shelves canned beans at Safeway.”

The “data-start” and “data-end” classes are the telltale clues that the content was generated by AI. Savvy SEOs are using that knowledge as part of their SEO audits to indentify AI-generated content that was directly copied and pasted into their WordPress editor.

Yoast SEO Premium Injects AI Classes

Alan Bleiweiss, known for content audits, called attention to the fact that Yoast SEO was injecting the “data-start” and “data-end” HTML classes into content. Alan called them “wrappers” but they’re technically HTML classes.

He posted:

“UPDATE

Yoast Plug-in pushed live without proper QA. Injecting AI wrappers without site owner permission.

Fortunately, according to Carolyn Shelby they’re working on a fix.

But tool providers need to do better.”

Alan indicated that no clarification was given as to how those classes were injected but the bug was limited to Yoast SEO Premium because the free version does not contain the necessary AI text generation feature (Yoast AI Optimize).

Yoast Pushes Update To Fix Bug

Yoast swiftly pushed an update, version 25.3.1, to fix the issue so that AI-generated content created by Yoast SEO Premium does not contain the classes. Happily, the updated plugin also removes the telltale HTML classes.

According to the Yoast SEO blog post announcement:

“Recently, we announced the rollout of Yoast AI Optimize for the Classic Editor in WordPress. …During the initial rollout, we discovered a technical issue where unintended classes were being added to content for some users. While these added classes are harmless and do not impact the functionality or appearance of your content, they should not have been added, that’s on us.

We take this seriously, and to maintain the quality you expect, we’ve been actively working on a solution. We’re pleased to share that a fix has now been released, and the issue has been resolved. For users already affected, we are automatically cleaning up the unintended classes as part of the fix, no action is needed on your part.”

The functionality was rolled out on June 2nd, which means that sites with affected content have been out there for at most two weeks.

The free version of the plugin has also been updated. The changelog offers this explanation:

“This is a maintenance release which is required to align with changes to Yoast SEO Premium 25.3.1.”

Can This Have Impacted Rankings?

It’s probably unlikely that this has affected rankings but at this point it’s unknown if Google would have noticed.  Google would have to specifically look for those classes which in themselves do not indicate anything about content quality. So again, it’s probably unlikely that this bug had an effect on search rankings.

Nevertheless users of the premium version of the Yoast SEO Plugin should update immediately to version 25.3.1 to fix any potential issues from this bug and users of the free version should update their versions as well, even though it’s not affected.

Could Buggy Release Have Been Prevented?

The AI class injection issue was only recently discovered, although it may have been out there for a while (since the introduction of the feature in August 2024). Changes to the content, site structure, and the underlying HTML should be something that all plugin developers check for before releasing a plugin to users.

This is especially true for the developers of the Yoast SEO plugin, because they have prior experience pushing out a troubled update that caused discernable changes to a website.

• Yoast SEO published an update in March 2022 that created duplicate sitemaps.
• In March 2018, Yoast SEO published a buggy update that created hundreds to thousands of thin pages, one page for each image uploaded to a website. That last issue went undetected for three months, as SEOs gradually began noticing thousands of new pages being generated.

This then is at least the third time that Yoast has pushed a buggy update that could have been avoided if they had tested the plugin before pushing it live. All it takes is to check whether a test site remains the same before and after an update. Given the stakes with AI-generated content, the output of the generated content and the underlying code is something that should have been tested.

Featured Image by Shutterstock/Jihan Nafiaa Zahri

https://www.searchenginejournal.com/yoast-seo-plugin-bug-injects-hidden-ai-html-classes/549311/