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Google Can’t Provide Details About Core Algorithm Updates

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Google Can't Provide Details About Core Algorithm Updates


Announcements about core algorithm updates are unlikely to get more detailed in the future, as Google says it can’t provide specific information.

Google has the details internally, but it can’t release the information publicly.

This was revealed in the latest episode of the Search Off The Record podcast with John Mueller, Martin Splitt, and Gary Illyes of Google’s Search Relations team.

Illyes is particularly frustrated by the fact that the team can’t give more information to the community when a core update is announced.

He questions what value there is in even announcing core updates if they can’t provide any guidance beyond telling people to review Google’s Webmaster Guidelines.

Based on the discussion it sounds like every announcement of a core update is going to be repeat of the one before it.

Google’s Search Relations team empathizes with everyone concerned about core updates, and wishes they could be more helpful to those impacted. But their hands are tied.

Here are some highlights from the discussion on core updates.

Google Knows What’s In A Core Update, But It Can’t Tell You

Illyes says the team behind core updates knows what’s in them:

“Well, our team generally knows what we are doing when we are doing core updates or what the things in the core updates do, more specifically. And in the vast majority of the cases, the things are just focusing on the guidelines that we’ve been publishing for the past 20 years.

So basically, write good content, right, don’t buy links, whatever, I don’t know. So every single time we do one of these core updates, we are basically saying that… follow our guidelines, and that’s also our advice.”

Illyes questions the benefit of announcing core updates when the team can’t provide specific details.

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He continues:

“… If we could give more guidance or more information about what’s in an update or how… Or what kind of sites it’s affecting or content it’s affecting, then I would be all for it, but at the moment we cannot.”

“And at the moment, we are just saying that: ‘Hello, there was a core update or incoming core update in two hours.’ And then four weeks later, we are like: ‘Yeah, we are finished with this core update.’”

In short — communication about core updates is limited to when they’ve started rolling out and when they’ve finished rolling out.

That’s the way it has always been up to now, and that’s likely all Google will be able to say about them in the future.

Misconceptions About Core Updates

Given that there’s so little information available about core updates, there tends to be a lot of misconceptions about them.

One of the misconceptions is that core updates are designed to punish websites.

Illyes wants to make it clear that’s not the case:

“And the thing I wanted to say is that there’s also a misconception about core updates. I think that it’s a punitive thing. It’s basically punishing sites. Which is not the case, but rather, we are optimizing our relevancy algorithms, for example, or quality, or algorithms that assess quality of a site/page/content. And what we are trying to do is give users better results in some sense, right?”

Inevitably, core updates will have a positive effect on some sites, while having a negative effect on others.

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When a site is negatively impacted by a core update it’s not necessarily because it did anything wrong, Illyes says:

“So, it might be that those sites that were affected negatively by a core update didn’t actually do anything wrong, but rather, our algorithms changed and that is very hard to explain, and also swallow, I imagine.

Because if you are publishing content and you’ve been publishing content for five years already, and you have a follower base and whatever, and suddenly, you rank lower and some competitors and ranking higher because Google made a change. That’s not easy to accept, I guess.”

If you find your site ranking lower after a core update it doesn’t mean you’re publishing bad content, or that there’s anything on your site you need to fix.

It’s more that other sites were “awarded” for publishing better content. Such as articles with greater depth, or articles that are more relevant to a specific query.

For more on recovering from core updates, see this advice Google has provided in the past:

Source: Search Off The Record


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Are Contextual Links A Google Ranking Factor?

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Are Contextual Links A Google Ranking Factor?


Inbound links are a ranking signal that can vary greatly in terms of how they’re weighted by Google.

One of the key attributes that experts say can separate a high value link from a low value link is the context in which it appears.

When a link is placed within relevant content, it’s thought to have a greater impact on rankings than a link randomly inserted within unrelated text.

Is there any bearing to that claim?

Let’s dive deeper into what has been said about contextual links as a ranking factor to see whether there’s any evidence to support those claims.

The Claim: Contextual Links Are A Ranking Factor

A “contextual link” refers to an inbound link pointing to a URL that’s relevant to the content in which the link appears.

When an article links to a source to provide additional context for the reader, for example, that’s a contextual link.

Contextual links add value rather than being a distraction.

They should flow naturally with the content, giving the reader some clues about the page they’re being directed to.

Not to be confused with anchor text, which refers to the clickable part of a link, a contextual link is defined by the surrounding text.

A link’s anchor text could be related to the webpage it’s pointing to, but if it’s surrounded by content that’s otherwise irrelevant then it doesn’t qualify as a contextual link.

Contextual links are said to be a Google ranking factor, with claims that they’re weighted higher by the search engine than other types of links.

One of the reasons why Google might care about context when it comes to links is because of the experience it creates for users.

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When a user clicks a link and lands on a page related to what they were previously looking at, it’s a better experience than getting directed to a webpage they aren’t interested in.

Modern guides to link building all recommend getting links from relevant URLs, as opposed to going out and placing links anywhere that will take them.

There’s now a greater emphasis on quality over quantity when it comes to link building, and a link is considered higher quality when its placement makes sense in context.

One high quality contextual link can, in theory, be worth more than multiple lower quality links.

That’s why experts advise site owners to gain at least a few contextual links, as that will get them further than building dozens of random links.

If Google weights the quality of links higher or lower based on context, it would mean Google’s crawlers can understand webpages and assess how closely they relate to other URLs on the web.

Is there any evidence to support this?

The Evidence For Contextual Links As A Ranking Factor

Evidence in support of contextual links as a ranking factor can be traced back to 2012 with the launch of the Penguin algorithm update.

Google’s original algorithm, PageRank, was built entirely on links. The more links pointing to a website, the more authority it was considered to have.

Websites could catapult their site up to the top of Google’s search results by building as many links as possible. It didn’t matter if the links were contextual or arbitrary.

Google’s PageRank algorithm wasn’t as selective about which links it valued (or devalued) over others until it was augmented with the Penguin update.

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Penguin brought a number of changes to Google’s algorithm that made it more difficult to manipulate search rankings through spammy link building practices.

In Google’s announcement of the launch of Penguin, former search engineer Matt Cutts highlighted a specific example of the link spam it’s designed to target.

This example depicts the exact opposite of a contextual link, with Cutts saying:

“Here’s an example of a site with unusual linking patterns that is also affected by this change. Notice that if you try to read the text aloud you’ll discover that the outgoing links are completely unrelated to the actual content, and in fact, the page text has been “spun” beyond recognition.”

A contextual link, on the other hand, looks like the one a few paragraphs above linking to Google’s blog post.

Links with context share the following characteristics:

  • Placement fits in naturally with the content.
  • Linked URL is relevant to the article.
  • Reader knows where they’re going when they click on it.

All of the documentation Google has published about Penguin over the years is the strongest evidence available in support of contextual links as a ranking factor.

See: A Complete Guide to the Google Penguin Algorithm Update

Google will never outright say “contextual link building is a ranking factor,” however, because the company discourages any deliberate link building at all.

As Cutts adds at the end of his Penguin announcement, Google would prefer to see webpages acquire links organically:

“We want people doing white hat search engine optimization (or even no search engine optimization at all) to be free to focus on creating amazing, compelling web sites.”

Contextual Links Are A Ranking Factor: Our Verdict

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Contextual links are probably a Google ranking factor.

A link is weighted higher when it’s used in context than if it’s randomly placed within unrelated content.

But that doesn’t necessarily mean links without context will negatively impact a site’s rankings.

External links are largely outside a site owner’s control.

If a website links to you out of context it’s not a cause for concern, because Google is capable of ignoring low value links.

On the other hand, if Google detects a pattern of unnatural links, then that could count against a site’s rankings.

If you have actively engaged in non-contextual link building in the past, it may be wise to consider using the disavow tool.


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Is It A Google Ranking Factor?

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Is It A Google Ranking Factor?


Latent semantic indexing (LSI) is an indexing and information retrieval method used to identify patterns in the relationships between terms and concepts.

With LSI, a mathematical technique is used to find semantically related terms within a collection of text (an index) where those relationships might otherwise be hidden (or latent).

And in that context, this sounds like it could be super important for SEO.

Right?

After all, Google is a massive index of information, and we’re hearing all kinds of things about semantic search and the importance of relevance in the search ranking algorithm.

If you’ve heard rumblings about latent semantic indexing in SEO or been advised to use LSI keywords, you aren’t alone.

But will LSI actually help improve your search rankings? Let’s take a look.

The Claim: Latent Semantic Indexing As A Ranking Factor

The claim is simple: Optimizing web content using LSI keywords helps Google better understand it and you’ll be rewarded with higher rankings.

Backlinko defines LSI keywords in this way:

“LSI (Latent Semantic Indexing) Keywords are conceptually related terms that search engines use to deeply understand content on a webpage.”

By using contextually related terms, you can deepen Google’s understanding of your content. Or so the story goes.

That resource goes on to make some pretty compelling arguments for LSI keywords:

  • Google relies on LSI keywords to understand content at such a deep level.”
  • LSI Keywords are NOT synonyms. Instead, they’re terms that are closely tied to your target keyword.”
  • Google doesn’t ONLY bold terms that exactly match what you just searched for (in search results). They also bold words and phrases that are similar. Needless to say, these are LSI keywords that you want to sprinkle into your content.”

Does this practice of “sprinkling” terms closely related to your target keyword help improve your rankings via LSI?

The Evidence For LSI As A Ranking Factor

Relevance is identified as one of five key factors that help Google determine which result is the best answer for any given query.

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As Google explains is its How Search Works resource:

“To return relevant results for your query, we first need to establish what information you’re looking forーthe intent behind your query.”

Once intent has been established:

“…algorithms analyze the content of webpages to assess whether the page contains information that might be relevant to what you are looking for.”

Google goes on to explain that the “most basic signal” of relevance is that the keywords used in the search query appear on the page. That makes sense – if you aren’t using the keywords the searcher is looking for, how could Google tell you’re the best answer?

Now, this is where some believe LSI comes into play.

If using keywords is a signal of relevance, using just the right keywords must be a stronger signal.

There are purpose-build tools dedicated to helping you find these LSI keywords, and believers in this tactic recommend using all kinds of other keyword research tactics to identify them, as well.

The Evidence Against LSI As A Ranking Factor

Google’s John Mueller has been crystal clear on this one:

“…we have no concept of LSI keywords. So that’s something you can completely ignore.”

There’s a healthy skepticism in SEO that Google may say things to lead us astray in order to protect the integrity of the algorithm. So let’s dig in here.

First, it’s important to understand what LSI is and where it came from.

Latent semantic structure emerged as a methodology for retrieving textual objects from files stored in a computer system in the late 1980s. As such, it’s an example of one of the earlier information retrieval (IR) concepts available to programmers.

As computer storage capacity improved and electronically available sets of data grew in size, it became more difficult to locate exactly what one was looking for in that collection.

Researchers described the problem they were trying to solve in a patent application filed September 15, 1988:

“Most systems still require a user or provider of information to specify explicit relationships and links between data objects or text objects, thereby making the systems tedious to use or to apply to large, heterogeneous computer information files whose content may be unfamiliar to the user.”

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Keyword matching was being used in IR at the time, but its limitations were evident long before Google came along.

Too often, the words a person used to search for the information they sought were not exact matches for the words used in the indexed information.

There are two reasons for this:

  • Synonymy: the diverse range of words used to describe a single object or idea results in relevant results being missed.
  • Polysemy: the different meanings of a single word results in irrelevant results being retrieved.

These are still issues today, and you can imagine what a massive headache it is for Google.

However, the methodologies and technology Google uses to solve for relevance long ago moved on from LSI.

What LSI did was automatically create a “semantic space” for information retrieval.

As the patent explains, LSI treated this unreliability of association data as a statistical problem.

Without getting too into the weeds, these researchers essentially believed that there was a hidden underlying latent semantic structure they could tease out of word usage data.

Doing so would reveal the latent meaning and enable the system to bring back more relevant results – and only the most relevant results – even if there’s no exact keyword match.

Here’s what that LSI process actually looks like:

Image created by author, January 2022

And here’s the most important thing you should note about the above illustration of this methodology from the patent application: there are two separate processes happening.

First, the collection or index undergoes Latent Semantic Analysis.

Second, the query is analyzed and the already-processed index is then searched for similarities.

And that’s where the fundamental problem with LSI as a Google search ranking signal lies.

Google’s index is massive at hundreds of billions of pages, and it’s growing constantly.

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Each time a user inputs a query, Google is sorting through its index in a fraction of a second to find the best answer.

Using the above methodology in the algorithm would require that Google:

  1. Recreate that semantic space using LSA across its entire index.
  2. Analyze the semantic meaning of the query.
  3. Find all similarities between the semantic meaning of the query and documents in the semantic space created from analyzing the entire index.
  4. Sort and rank those results.

That’s a gross oversimplification, but the point is that this isn’t a scalable process.

This would be super useful for small collections of information. It was helpful for surfacing relevant reports inside a company’s computerized archive of technical documentation, for example.

The patent application illustrates how LSI works using a collection of nine documents. That’s what it was designed to do. LSI is primitive in terms of computerized information retrieval.

Latent Semantic Indexing As A Ranking Factor: Our Verdict

Latent Semantic Indexing (LSI): Is It A Google Ranking Factor?

While the underlying principles of eliminating noise by determining semantic relevance have surely informed developments in search ranking since LSA/LSI was patented, LSI itself has no useful application in SEO today.

It hasn’t been ruled out completely, but there is no evidence that Google has ever used LSI to rank results. And Google definitely isn’t using LSI or LSI keywords today to rank search results.

Those who recommend using LSI keywords are latching on to a concept they don’t quite understand in an effort to explain why the ways in which words are related (or not) is important in SEO.

Relevance and intent are foundational considerations in Google’s search ranking algorithm.

Those are two of the big questions they’re trying to solve for in surfacing the best answer for any query.

Synonymy and polysemy are still major challenges.

Semantics – that is, our understanding of the various meanings of words and how they’re related – is essential in producing more relevant search results.

But LSI has nothing to do with that.


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What Is a Google Broad Core Algorithm Update?

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What Is A Google Broad Core Algorithm Update?


When Google announces a broad core algorithm update, many SEO professionals find themselves asking what exactly changed (besides their rankings).

Google’s acknowledgment of core updates is always vague and doesn’t provide much detail other than to say the update occurred.

The SEO community is typically notified about core updates via the same standard tweets from Google’s Search Liaison.

There’s one announcement from Google when the update begins rolling out, and one on its conclusion, with few additional details in between (if any).

This invariably leaves SEO professionals and site owners asking many questions with respect to how their rankings were impacted by the core update.

To gain insight into what may have caused a site’s rankings to go up, down, or stay the same, it helps to understand what a broad core update is and how it differs from other types of algorithm updates.

After reading this article you’ll have a better idea of what a core update is designed to do, and how to recover from one if your rankings were impacted.

So, What Exactly Is A Core Update?

First, let me get the obligatory “Google makes hundreds of algorithm changes per year, often more than one per day” boilerplate out of the way.

Many of the named updates we hear about (Penguin, Panda, Pigeon, Fred, etc.) are implemented to address specific faults or issues in Google’s algorithms.

In the case of Penguin, it was link spam; in the case of Pigeon, it was local SEO spam.

They all had a specific purpose.

In these cases, Google (sometimes reluctantly) informed us what they were trying to accomplish or prevent with the algorithm update, and we were able to go back and remedy our sites.

A core update is different.

The way I understand it, a core update is a tweak or change to the main search algorithm itself.

You know, the one that has between 200 and 500 ranking factors and signals (depending on which SEO blog you’re reading today).

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What a core update means to me is that Google slightly tweaked the importance, order, weights, or values of these signals.

Because of that, they can’t come right out and tell us what changed without revealing the secret sauce.

The simplest way to visualize this would be to imagine 200 factors listed in order of importance.

Now imagine Google changing the order of 42 of those 200 factors.

Rankings would change, but it would be a combination of many things, not due to one specific factor or cause.

Obviously, it isn’t that simple, but that’s a good way to think about a core update.

Here’s a purely made up, slightly more complicated example of what Google wouldn’t tell us:

“In this core update, we increased the value of keywords in H1 tags by 2%, increased the value of HTTPS by 18%, decreased the value of keyword in title tag by 9%, changed the D value in our PageRank calculation from .85 to .70, and started using a TF-iDUF retrieval method for logged in users instead of the traditional TF-PDF method.”

(I swear these are real things. I just have no idea if they’re real things used by Google.)

For starters, many SEO pros wouldn’t understand it.

Basically, it means Google may have changed the way they calculate term importance on a page, or the weighing of links in PageRank, or both, or a whole bunch of other factors that they can’t talk about (without giving away the algorithm).

Put simply: Google changed the weight and importance of many ranking factors.

That’s the simple explanation.

At its most complex form, Google ran a new training set through their machine learning ranking model and quality raters picked this new set of results as more relevant than the previous set, and the engineers have no idea what weights changed or how they changed because that’s just how machine learning works.

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(We all know Google uses quality raters to rate search results. These ratings are how they choose one algorithm change over another – not how they rate your site. Whether they feed this into machine learning is anybody’s guess. But it’s one possibility.)

It’s likely some random combination of weighting delivered more relevant results for the quality raters, so they tested it more, the test results confirmed it, and they pushed it live.

How Can You Recover From A Core Update?

Unlike a major named update that targeted specific things, a core update may tweak the values of everything.

Because websites are weighted against other websites relevant to your query (engineers call this a corpus) the reason your site dropped could be entirely different than the reason somebody else’s increased or decreased in rankings.

To put it simply, Google isn’t telling you how to “recover” because it’s likely a different answer for every website and query.

It all depends on what everybody else trying to rank for your query is doing.

Does every one of them but you have their keyword in the H1 tag? If so then that could be a contributing factor.

Do you all do that already? Then that probably carries less weight for that corpus of results.

It’s very likely that this algorithm update didn’t “penalize” you for something at all. It most likely just rewarded another site more for something else.

Maybe you were killing it with internal anchor text and they were doing a great job of formatting content to match user intent – and Google shifted the weights so that content formatting was slightly higher and internal anchor text was slightly lower.

(Again, hypothetical examples here.)

In reality, it was probably several minor tweaks that, when combined, tipped the scales slightly in favor of one site or another (think of our reordered list here).

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Finding that “something else” that is helping your competitors isn’t easy – but it’s what keeps SEO professionals in the business.

Next Steps And Action Items

Rankings are down after a core update – now what?

Your next step is to gather intel on the pages that are ranking where your site used to be.

Conduct a SERP analysis to find positive correlations between pages that are ranking higher for queries where your site is now lower.

Try not to overanalyze the technical details, such as how fast each page loads or what their core web vitals scores are.

Pay attention to the content itself. As you go through it, ask yourself questions like:

  • Does it provide a better answer to the query than your article?
  • Does the content contain more recent data and current stats than yours?
  • Are there pictures and videos that help bring the content to life for the reader?

Google aims to serve content that provides the best and most complete answers to searchers’ queries. Relevance is the one ranking factor that will always win out over all others.

Take an honest look at your content to see if it’s as relevant today as it was prior to the core algorithm update.

From there you’ll have an idea of what needs improvement.

The best advice for conquering core updates?

Keep focusing on:

  • User intent.
  • Quality content.
  • Clean architecture.
  • Google’s guidelines.

Finally, don’t stop improving your site once you reach Position 1, because the site in Position 2 isn’t going to stop.

Yeah, I know, it’s not the answer anybody wants and it sounds like Google propaganda. I swear it’s not.

It’s just the reality of what a core update is.

Nobody said SEO was easy.

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