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Google Confirms a Way to Hide Internal Links via @martinibuster

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Google’s John Mueller answered a question about links in the button element, confirming that Google can’t see them. Some SEOs have been hiding internal links in the button element in order to block PageRank from “unimportant” pages. Mueller’s answer seems to confirm that the tactic for hiding links from Google works.

But just because something can be done, should it?

Screenshot of Google's John MuellerGoogle’s John Mueller discussing links in the button HTML element.Screenshot of Google's John Mueller

PRG Pattern for Hiding Links from Google

PageRank Sculpting, the practice of hiding internal links from Google, is not a tactic that I’ve ever endorsed or recommended.

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However it’s a tactic that many SEOs are interested in.

The concept of the Post/Redirect/Get Pattern (PRG Pattern) for hiding links is the topic raised by the person asking the question and the answer given by John Mueller.

The phrase “PRG Pattern” is never mentioned, but the concept of PRG Pattern is what they are both discussing.

The PRG pattern, sometimes referred to as “The New Nofollow,” is a way to hide internal links from Google by using a button HTML element.

Reasons to Hide Links with the PRG Pattern

There are legitimate reasons to hide links this way in ecommerce stores. Some stores may generate multiple URLs for the same product page.  By using this method, a store owner can hide those links from Google and prevent them from having to deal with them. There are even Magento extensions that help to create these kinds of links for online stores.

Another reason some SEOs use the tactic is to keep PageRank from flowing to certain pages that don’t contribute to rankings.  Examples of the kinds of pages that some SEOs block are pages about privacy or the terms of service.

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The ultimate goal of this tactic is to maximize the amount of PageRank flowing to the pages that matter.

As I stated earlier however, this is not a tactic that I recommend.

PRG Pattern – The New Nofollow

PageRank is the name given to a value that’s assigned to a link that is passed from one link to another link. The more PageRank a page accrues the more trustworthy and popular Google’s algorithm assumes it to be, which helps in rankings.

The practice of limiting what pages receive PageRank is called PageRank Sculpting. The goal of PageRank sculpting is to hide links from Google so that no PageRank is sent to those pages.

How Does the PRG Pattern Link Sculpting Work?

The PRG Pattern is basically a form button, like a submit button. For example, when a site visitor submits a form the form redirects the visitor to a “Thank you” page that thanks them for submitting the form.

When the person asking the question references a “button tag” what they are talking about is the button HTML element. The button HTML element is associated with forms, like a contact form, for example.

The PRG Pattern for conserving PageRank works in a similar way to a contact form button. The PRG Pattern “link” is a form button that redirects the site visitor to another internal web page.

To the site visitor the button is just a navigational element that might be labeled with the phrase, “Privacy Policy.

Does Button Element Negatively Affect SEO?

The question asked is if using a button HTML element for internal linking is harmful to SEO.

Here’s the question:

“Does it negatively affect SEO for internal linking if an anchor tag only contains a button tag?

Does Googlebot take the text inside the button tag into account as a signal for internal links?

Or would it be better to use plain text inside of an anchor tag?”

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Google’s John Mueller answers the question, confirming that Google does not click buttons to see where they lead to.

John Mueller’s answer:

“So at least as far as I understand it, by default, a button element on a page is essentially tied to a form element.

And you can use JavaScript to trigger a kind of a navigation to a specific URL, which makes it kind of like a link.

But, essentially, Googlebot won’t click on these buttons to see what happens.

So we would not see that there’s a link associated to another URL within your website.”

If what John Mueller says in his answer is correct, then it appears that the PRG Pattern for Hiding Links could be used to hide pages from Google so that PageRank does not flow to so-called non-essential pages.

John Mueller continued his answer, suggesting a way to use Cascading Style Sheets (CSS) to create the image of a form that contains a link that Google can follow.

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Of course, if the goal of the publisher is to hide links from Google, then that’s not something they would be interested in.

Mueller continued:

“So in that regard, if you want to use …something that looks like a button for internal navigation then I would use normal HTML links and just style it with CSS to make it look like a button rather than to use button elements in HTML and add JavaScript that kind of makes them act like a link.”

Can PageRank Be Sculpted Using the PRG Pattern?

According to John Mueller, if what he says is correct, then it may be that the PRG Pattern method may be a way to hide links from Google and keep PageRank from flowing to them.

Mueller didn’t indicate that this is something that was “harmful to SEO” either.

The idea of PageRank is about one site voting for another site. That’s a powerful signal.

The distribution of PageRank to internal pages may not be as strong a signal as a link from another site to an important page of another site.  A good site structure is important for helping Google find pages to crawl.

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Although SEOs will tend to focus on squeezing every possible advantage, in my opinion, focusing on promoting a site and creating a good internal linking structure is a far better use of time than PageRank sculpting.

Citation

Watch Google’s John Mueller say Google can’t see links in button HTML elements

The segment begins at the 42:.03 minute mark.

[embedded content]

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Google December 2021 Product Review Update via @sejournal, @martinibuster

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Google announced an English language product review update is rolling out today, Wednesday December 1, 2021. Product review pages that have made improvements since the last product review update may see them reflected in the new update.

The update is called the December 201 Product Review Update and will take three weeks to fully roll out.

This update is preceded by a Spam Update in early November and a Core Algorithm Update that finished rolling out at the end of November.

While some may feel it ill-timed or mean for Google to roll out updates during the busiest shopping season, so far these updates have not been especially disruptive.

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Yet it would be most unfortunate if legitimate product review sites unintentionally lost rankings during this critical time of the year.

A tweet from Google Search Central announced:

“Our December 2021 product reviews update is now rolling out for English-language pages. It will take about three weeks to complete.”

Google Developer Advocate Alan Kent tweeted:

“It is one of many ranking signals, but certainly the goal is to reward authentic high quality reviews. The docs page lists our recommendations for good reviews.”

Alan tweeted clarification of what kinds of sites will be affected by the product reviews update:

“Mainly relevant to sites that post articles reviewing products. Think of sites like “best TVs under $200″.com. Goal is to improve the quality and usefulness of reviews we show users.”

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The response on Twitter generally took the announcement in stride:

Product Review Page Ranking Assessment

Google’s announcement makes reference to an “automated assessment” that is specific to product reviews. It also notes that product review pages will also be ranked by the other ranking factors common to other web pages.

“…note that our automated assessment of product review content is only one of many factors used in ranking content, so changes can happen at any time for various reasons.”

New Product Review Best Practices

Google also gave an advanced warning that they will be introducing two new product review requirements that are clearly aimed at fake product reviews.

The first requirement is that a product review provide on-page evidence that a product has actually been handled and reviewed.

Many low quality reviews are clearly affiliate sites posting bogus reviews that are closer to rewritten versions of the product specifications.

The second requirement is that product reviews offer multiple buying options.

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Google’s product review update stated:

“Users have told us that they trust reviews with evidence of products actually being tested, and prefer to have more options to purchase the product.

Provide evidence such as visuals, audio, or other links of your own experience with the product, to support your expertise and reinforce the authenticity of your review.

Include links to multiple sellers to give the reader the option to purchase from their merchant of choice.”

Google didn’t call these best practices ranking factors but does say that these “best practices” will be folded into a future product reviews update.

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So these two best practices can probably be considered ranking factors.

The new documentation is called, Write high quality product reviews.

The best practices page highlights requirements that seem designed to promote actual reviews and eliminate fake reviews.

Here is a sample:

  • Share quantitative measurements about how a product measures up in various categories of performance.
  • Describe how a product has evolved from previous models or releases to provide improvements, address issues, or otherwise help users in making a purchase decision.
  • Describe key choices in how a product has been designed and their effect on the users beyond what the manufacturer says.
  • Include links to other useful resources (your own or from other sites) to help a reader make a decision.

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Promoting Quality Product Reviews

Many products are expensive to review, such as kayaks, which is why there are so many fake reviews that do not feature original images of the products because no kayak was actually reviewed.

One has to wonder if these new requirements could backfire by causing fake review sites to respond by adding fake hands-on assessment content and images.

Citations

Announcement of Product Review Update

Product reviews update and your site

Read Google’s Product Reviews Best Practices

Write high quality product reviews

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Google’s New Pathways AI Is Closer to Mammalian Brain via @sejournal, @martinibuster

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Google announced a new AI architecture that powerfully expands Google’s AI computing ability in a profound way. The new AI architecture is is a single model that can be trained to do millions of things, which Google says is closer to a mammalian brain.

Google Pathways AI

The announcement by Google states that the current state of AI is to train a machine to do one thing very well, like to recognize images or understand the sound of an animal.

So in order to understand sight and sound it would take two different AI models to accomplish the two tasks.

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The new AI architecture takes a different path by training it to generalize by learning skills that can be applied across different tasks.

Google explains how it works:

“…we’d like to train one model that can not only handle many separate tasks, but also draw upon and combine its existing skills to learn new tasks faster and more effectively.

That way what a model learns by training on one task – say, learning how aerial images can predict the elevation of a landscape – could help it learn another task — say, predicting how flood waters will flow through that terrain.

We want a model to have different capabilities that can be called upon as needed, and stitched together to perform new, more complex tasks – a bit closer to the way the mammalian brain generalizes across tasks.”

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An AI That Can Train For Multiple Senses

Current AI models train for single senses, like sight or hearing but not both. Google states that such a model will be able to understand a concept in all the relevant senses together.

With Pathways Google can understand text, images and speech together in a single AI model.

Pathways Works Like The Human Brain

The human brain only uses a small amount of its processing power to complete tasks, using the specialized parts and not the entire brain network.

Google’s new Pathways AI will accomplish tasks in a similar way, which will make more energy efficient, be able to learn more and do it all faster than older models.

“There are close to a hundred billion neurons in your brain, but you rely on a small fraction of them to interpret this sentence.

AI can work the same way.

We can build a single model that is “sparsely” activated, which means only small pathways through the network are called into action as needed.”

Pathways AI Will Solve Multiple Problems

The purpose of Pathways is bigger than search. Google says that it can be adapted to solving many problems, including problems that we haven’t yet faced.

“…we’re crafting the kind of next-generation AI system that can quickly adapt to new needs and solve new problems all around the world as they arise, helping humanity make the most of the future ahead of us.”

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Google Pathways AI Architecture

Google’s blog post does not say if Pathways has been activated in any system yet. The announcement says that Google has the ability now to create these systems and that they will build them.

Google also states that they have teams that are working on designing the “next-generation” AI architecture.

Google explicitly says they are “crafting” this new AI architecture:

“That’s why we’re building Pathways. Pathways will enable a single AI system to generalize across thousands or millions of tasks, to understand different types of data, and to do so with remarkable efficiency…”

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Google has been publishing research papers on machine learning technologies that can learn to generalize, one of which is called FLAN.

FLAN can train a machine to learn how to complete a task and apply what it learned to other tasks, very much like what is described in the article about Pathways.

This new Pathways AI architecture may be very close to realization if it’s not already here in some form.

Citation

Read Google’s Announcement Of A New AI Architecture

Introducing Pathways: A next-generation AI architecture

Read About New Google Research Paper About FLAN

Google Research Develops Better Machine Learning

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Google November Core Update Is Over – What Happened? via @sejournal, @martinibuster

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It’s official, Google’s November core algorithm update is over today on Tuesday, November 30, 2021, the day after the popular Cyber Monday shopping day. Sites that experienced an up or downward shift in rankings should not expect additional changes to their status until the next algorithm update.

Google announced the end of the core update rollout on Twitter:

“The November 2021 Core Update is now rolling out live. As is typical with these updates, it will typically take about one to two weeks to fully roll out.”

It’s possible that changes in traffic around the time of the algorithm might not be related to the update. Coincidences do happen but it’s a slim hope.

The changes seen today can be said to be permanent and until the next update there should only be the daily up and down in rankings that are characteristic of a constantly updated search index.

Unlike in the past where the search index remained fixed for a month at a time, today’s search engine is more dynamic and responsive to links and content.

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What doesn’t change is the underlying processes themselves.

Read more: Google Update Slapped Your Rankings: What’s Next

What Was The November Update?

Search Community Shares Insights

Many search marketers agreed that the November core algorithm update did not have the disruptive impact of a major update.

Japan-based SEO Kenichi Suzuki (@suzukik)

Kenichi Suzuki, a respected Japanese search marketer offered his observations of the impact to the Google search results in Japan.

Kenichi shared:

“The November 2021 Core Update seems to have made much less impact on rankings, compared with other core updates.

The ranking changes are not that different than daily fluctuations.

That said, we’ve seen Google look at who (author/company) publishes the content more carefully.”

Jason Barnard (@jasonmbarnard)

Jason Barnard noticed wild fluctuations in Google’s Knowledge Graph on November 16th, the day before the update:

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Is that related to the update that would be released on the following day?

Nobody knows for certain but it’s an interesting sideshow accompanying the main event.

Jason offered his thoughts on what happened in the Knowledge Graph:

“Here we had Google announce a core update on the 17th of November and the knowledge graph went crazy beginning the day before.

There was also a “deepening” of the Knowledge Graph that same day (ie queries returned 6% more results on average…).

That number had not changed for at least 2 years. So that 6% is big news.”

Ammon Johns (@Ammon_Johns)

I asked widely respected search marketer, Ammon Johns, about the update.

Ammon shared:

“There’s no single unifying theme (yet), no suddenly recurring problem or symptom surfacing in the various SEO groups.

Only the ongoing mass of issues many smaller site owners had in the weeks running up to the update where crawling was reduced, and sites with lower crawl priorities found they couldn’t get their new content indexed.”

Ammon is referencing the growing concern in the worldwide search marketing community about how Google seems to be indexing less content.

That’s something that began peaking in October 2021 and continues to be a source of anxiety for many publishers.

Steven Kang (@SEOSignalsLab)

Steven Kang is the administrator of the wildly popular SEO Signals Lab Facebook community. His community has thousands of members and countless discussions every day. If anyone has the pulse of the search community on social media, it’s Steven Kang.

Here is what Steve observed about the core update:

“I’m seeing mixed results. Some went up and some down. I’m not seeing the seismic difference…”

Jim Boykin (@jimboykin) – Founder of Internet Marketing Ninjas

Jim Boykin has been in SEO for over twenty years and one thing I have observed about Jim is that he’s open minded to changes and is quick to adapt, which to me makes his opinions matter all the more.

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These are Jim’s observations on Google’s November update:

“We had 12 clients that had really nice ranking/traffic improvements, and about 25 clients that didn’t see much either way, and we had 7 clients that saw a bit of a drop. About 5 of the 7 that dropped fell 1-3 ranking positions lower. Two of those seven had bigger drops.

Overall, this is just another algo update… there will always be winners and losers each time… I just try to keep making the sites better and stress doing that to those who were negatively effected.”

Bill Hartzer (@bhartzer)

Bill Hartzer, another search marketer with over twenty years of experience concurred with the observation that this update had a small impact.

Bill observed:

“I feel as if it’s been a low impact update.”

Was The Update Partly An Infrastructure Update?

This update is generally agreed by many in the search industry to have been a relatively mild one. That in itself is very interesting because it could suggest a shift in the underlying algorithm architecture where it still does the same thing, relatively, but it does it more efficiently and faster.

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The core algorithm update was preceded by a spam update which presumably cleared the table of negative influences to the search index, to make the search index more pure and less spam.

FLAN Machine Learning Research Paper

It’s especially interesting because Google AI has published research on new machine learning models that do not specialize at doing many things really well, which is a change from previous models that did one thing really well and required an army of multiple models to do all these different things.

One such model is called FLAN that was introduced as a research paper in October. What FLAN does is focuses the natural language training on solving different kinds tasks and then generalizing the method so that it can apply to a wide variety of tasks.

Read More: FLAN: Google Research Develops Better Machine Learning

Google Introduced Pathways, A New AI Architecture

The November core algorithm update began on November 17, 2021 and finished nearly two weeks later on November 30th.

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If Google were to introduce a new more efficient way to accomplish the same thing it was already doing, then that might require clearing the board of spam with a spam update and then introducing the new algorithm architecture slowly across the entire system.

Perhaps not coincidentally, around the same time as the FLAN research was published Google officially announced a new AI Architecture called Pathways that seems to do many of things that FLAN claims to improve on.

The Google Pathways announcement states:

“Too often, machine learning systems overspecialize at individual tasks, when they could excel at many.

That’s why we’re building Pathways—a new AI architecture that will handle many tasks at once, learn new tasks quickly and reflect a better understanding of the world.

….Today’s AI models are typically trained to do only one thing.

Pathways will enable us to train a single model to do thousands or millions of things.”

One thing to note is that the Pathways article, published in October 2021, refers to things they are going to build, not to things that they have already introduced.

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So it’s entirely possible that Pathways was not introduced in the mid-November 2021 core algorithm update.

Ammon Johns Is Reminded of Hummingbird Update

Ammon Johns remarked that the November 2021 core algorithm update felt like an infrastructure update.

Ammon shared his thoughts:

“I’m reminded a bit of the Hummingbird Update, where it had actually been live for a couple of months or something like that before the news broke, and nobody had noticed.”

I agree with Ammon. In general terms, the November 2021 update had a relatively gentle impact on the search results.

And that is what makes it feel like an infrastructure related update that makes Google’s algorithms more efficient.

Google November 2021 Core Update Takeaways

I think most people would agree that Google’s core update was somewhat odd.

  • Kenichi Suzuki, the search marketer in Japan, feels that Google was focusing a little more on authorship signals.
  • Jason Barnard noticed extreme volatility in the Knowledge Graph, sharing that Google was returning 6% more knowledge graph-based results. Jason says a 6% increase is huge and a scale he’s never seen before.
  • Ammon Johns feels, like I do, that the quiet nature of this update might indicate that Google made more infrastructure-related changes.
  • Social media has been relatively quiet this update, suggesting that whatever impact it had was not widely felt  in the way that a major update would feel.
  • Lastly, Google published an article and a research paper that both signal improvements to Google’s algorithms that can dramatically speed up current question answering tasks and in the future greatly increase Google’s ability to answer more complex questions.

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