SEO

Is It A Google Ranking Factor?

Published

2 years ago

January 23, 2022

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.

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.”

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.

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:

Recreate that semantic space using LSA across its entire index.
Analyze the semantic meaning of the query.
Find all similarities between the semantic meaning of the query and documents in the semantic space created from analyzing the entire index.
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.

Featured Image: Paulo Bobita/Search Engine Journal

SEO

Big Update To Google’s Ranking Drop Documentation

Published

6 hours ago

April 27, 2024

Max

Google updates documentation for diagnosing ranking drops

Google updated their guidance with five changes on how to debug ranking drops. The new version contains over 400 more words that address small and large ranking drops. There’s room to quibble about some of the changes but overall the revised version is a step up from what it replaced.

Change# 1: Downplays Fixing Traffic Drops

The opening sentence was changed so that it offers less hope for bouncing back from an algorithmic traffic drop. Google also joined two sentences into one sentence in the revised version of the documentation.

The documentation previously said that most traffic drops can be reversed and that identifying the reasons for a drop aren’t straightforward. The part about most of them can be reversed was completely removed.

Here is the original two sentences:

“A drop in organic Search traffic can happen for several reasons, and most of them can be reversed. It may not be straightforward to understand what exactly happened to your site”

Now there’s no hope offered for “most of them can be reversed” and more emphasis on understanding what happened is not straightforward.

This is the new guidance

“A drop in organic Search traffic can happen for several reasons, and it may not be straightforward to understand what exactly happened to your site.”

Change #2 Security Or Spam Issues

Google updated the traffic graph illustrations so that they precisely align with the causes for each kind of traffic decline.

The previous version of the graph was labeled:

“Site-level technical issue (Manual Action, strong algorithmic changes)”

The problem with the previous label is that manual actions and strong algorithmic changes are not technical issues and the new version fixes that issue.

The updated version now reads:

“Large drop from an algorithmic update, site-wide security or spam issue”

Change #3 Technical Issues

There’s one more change to a graph label, also to make it more accurate.

This is how the previous graph was labeled:

“Page-level technical issue (algorithmic changes, market disruption)”

The updated graph is now labeled:

“Technical issue across your site, changing interests”

Now the graph and label are more specific as a sitewide change and “changing interests” is more general and covers a wider range of changes than market disruption. Changing interests includes market disruption (where a new product makes a previous one obsolete or less desirable) but it also includes products that go out of style or loses their trendiness.

Graph titled

Change #4 Google Adds New Guidance For Algorithmic Changes

The biggest change by far is their brand new section for algorithmic changes which replaces two smaller sections, one about policy violations and manual actions and a second one about algorithm changes.

The old version of this one section had 108 words. The updated version contains 443 words.

A section that’s particularly helpful is where the guidance splits algorithmic update damage into two categories.

Two New Categories:

Small drop in position? For example, dropping from position 2 to 4.
Large drop in position? For example, dropping from position 4 to 29.

The two new categories are perfect and align with what I’ve seen in the search results for sites that have lost rankings. The reasons for dropping up and down within the top ten are different from the reasons why a site drops completely out of the top ten.

I don’t agree with the guidance for large drops. They recommend reviewing your site for large drops, which is good advice for some sites that have lost rankings. But in other cases there’s nothing wrong with the site and this is where less experienced SEOs tend to be unable to fix the problems because there’s nothing wrong with the site. Recommendations for improving EEAT, adding author bios or filing link disavows do not solve what’s going on because there’s nothing wrong with the site. The problem is something else in some of the cases.

Here is the new guidance for debugging search position drops:

“Algorithmic update
Google is always improving how it assesses content and updating its search ranking and serving algorithms accordingly; core updates and other smaller updates may change how some pages perform in Google Search results. We post about notable improvements to our systems on our list of ranking updates page; check it to see if there’s anything that’s applicable to your site.
If you suspect a drop in traffic is due to an algorithmic update, it’s important to understand that there might not be anything fundamentally wrong with your content. To determine whether you need to make a change, review your top pages in Search Console and assess how they were ranking:
Small drop in position? For example, dropping from position 2 to 4.
Large drop in position? For example, dropping from position 4 to 29.
Keep in mind that positions aren’t static or fixed in place. Google’s search results are dynamic in nature because the open web itself is constantly changing with new and updated content. This constant change can cause both gains and drops in organic Search traffic.
Small drop in position
A small drop in position is when there’s a small shift in position in the top results (for example, dropping from position 2 to 4 for a search query). In Search Console, you might see a noticeable drop in traffic without a big change in impressions.
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Small fluctuations in position can happen at any time (including moving back up in position, without you needing to do anything). In fact, we recommend avoiding making radical changes if your page is already performing well.
Large drop in position
A large drop in position is when you see a notable drop out of the top results for a wide range of terms (for example, dropping from the top 10 results to position 29).
In cases like this, self-assess your whole website overall (not just individual pages) to make sure it’s helpful, reliable and people-first. If you’ve made changes to your site, it may take time to see an effect: some changes can take effect in a few days, while others could take several months. For example, it may take months before our systems determine that a site is now producing helpful content in the long term. In general, you’ll likely want to wait a few weeks to analyze your site in Search Console again to see if your efforts had a beneficial effect on ranking position.
Keep in mind that there’s no guarantee that changes you make to your website will result in noticeable impact in search results. If there’s more deserving content, it will continue to rank well with our systems.”

Change #5 Trivial Changes

The rest of the changes are relatively trivial but nonetheless makes the documentation more precise.

For example, one of the headings was changed from this:

You recently moved your site

To this new heading:

Site moves and migrations

Google’s Updated Ranking Drops Documentation

Google’s updated documentation is a well thought out but I think that the recommendations for large algorithmic drops are helpful for some cases and not helpful for other cases. I have 25 years of SEO experience and have experienced every single Google algorithm update. There are certain updates where the problem is not solved by trying to fix things and Google’s guidance used to be that sometimes there’s nothing to fix. The documentation is better but in my opinion it can be improved even further.

Read the new documentation here:

Debugging drops in Google Search traffic

Review the previous documentation:

Internet Archive Wayback Machine: Debugging drops in Google Search traffic

Featured Image by Shutterstock/Tomacco

SEO

Google March 2024 Core Update Officially Completed A Week Ago

Published

1 day ago

April 27, 2024

Max

Google has officially completed its March 2024 Core Update, ending over a month of ranking volatility across the web.

However, Google didn’t confirm the rollout’s conclusion on its data anomaly page until April 26—a whole week after the update was completed on April 19.

Many in the SEO community had been speculating for days about whether the turbulent update had wrapped up.

The delayed transparency exemplifies Google’s communication issues with publishers and the need for clarity during core updates

Google March 2024 Core Update Timeline & Status

First announced on March 5, the core algorithm update is complete as of April 19. It took 45 days to complete.

Unlike more routine core refreshes, Google warned this one was more complex.

Google’s documentation reads:

“As this is a complex update, the rollout may take up to a month. It’s likely there will be more fluctuations in rankings than with a regular core update, as different systems get fully updated and reinforce each other.”

The aftershocks were tangible, with some websites reporting losses of over 60% of their organic search traffic, according to data from industry observers.

The ripple effects also led to the deindexing of hundreds of sites that were allegedly violating Google’s guidelines.

Addressing Manipulation Attempts

In its official guidance, Google highlighted the criteria it looks for when targeting link spam and manipulation attempts:

Creating “low-value content” purely to garner manipulative links and inflate rankings.
Links intended to boost sites’ rankings artificially, including manipulative outgoing links.
The “repurposing” of expired domains with radically different content to game search visibility.

The updated guidelines warn:

“Any links that are intended to manipulate rankings in Google Search results may be considered link spam. This includes any behavior that manipulates links to your site or outgoing links from your site.”

John Mueller, a Search Advocate at Google, responded to the turbulence by advising publishers not to make rash changes while the core update was ongoing.

However, he suggested sites could proactively fix issues like unnatural paid links.

Mueller stated on Reddit:

“If you have noticed things that are worth improving on your site, I’d go ahead and get things done. The idea is not to make changes just for search engines, right? Your users will be happy if you can make things better even if search engines haven’t updated their view of your site yet.”

Emphasizing Quality Over Links

The core update made notable changes to how Google ranks websites.

Most significantly, Google reduced the importance of links in determining a website’s ranking.

In contrast to the description of links as “an important factor in determining relevancy,” Google’s updated spam policies stripped away the “important” designation, simply calling links “a factor.”

This change aligns with Google’s Gary Illyes’ statements that links aren’t among the top three most influential ranking signals.

Instead, Google is giving more weight to quality, credibility, and substantive content.

Consequently, long-running campaigns favoring low-quality link acquisition and keyword optimizations have been demoted.

With the update complete, SEOs and publishers are left to audit their strategies and websites to ensure alignment with Google’s new perspective on ranking.

Core Update Feedback

Google has opened a ranking feedback form related to this core update.

You can use this form until May 31 to provide feedback to Google’s Search team about any issues noticed after the core update.

While the feedback provided won’t be used to make changes for specific queries or websites, Google says it may help inform general improvements to its search ranking systems for future updates.

Google also updated its help documentation on “Debugging drops in Google Search traffic” to help people understand ranking changes after a core update.

Featured Image: Rohit-Tripathi/Shutterstock

FAQ

After the update, what steps should websites take to align with Google’s new ranking criteria?

After Google’s March 2024 Core Update, websites should:

Improve the quality, trustworthiness, and depth of their website content.
Stop heavily focusing on getting as many links as possible and prioritize relevant, high-quality links instead.
Fix any shady or spam-like SEO tactics on their sites.
Carefully review their SEO strategies to ensure they follow Google’s new guidelines.

SEO

Google Declares It The “Gemini Era” As Revenue Grows 15%

Published

2 days ago

April 26, 2024

Max

Alphabet Inc., Google’s parent company, announced its first quarter 2024 financial results today.

While Google reported double-digit growth in key revenue areas, the focus was on its AI developments, dubbed the “Gemini era” by CEO Sundar Pichai.

The Numbers: 15% Revenue Growth, Operating Margins Expand

Alphabet reported Q1 revenues of $80.5 billion, a 15% increase year-over-year, exceeding Wall Street’s projections.

Net income was $23.7 billion, with diluted earnings per share of $1.89. Operating margins expanded to 32%, up from 25% in the prior year.

Ruth Porat, Alphabet’s President and CFO, stated:

“Our strong financial results reflect revenue strength across the company and ongoing efforts to durably reengineer our cost base.”

Google’s core advertising units, such as Search and YouTube, drove growth. Google advertising revenues hit $61.7 billion for the quarter.

The Cloud division also maintained momentum, with revenues of $9.6 billion, up 28% year-over-year.

Pichai highlighted that YouTube and Cloud are expected to exit 2024 at a combined $100 billion annual revenue run rate.

Generative AI Integration in Search

Google experimented with AI-powered features in Search Labs before recently introducing AI overviews into the main search results page.

Regarding the gradual rollout, Pichai states:

“We are being measured in how we do this, focusing on areas where gen AI can improve the Search experience, while also prioritizing traffic to websites and merchants.”

Pichai reports that Google’s generative AI features have answered over a billion queries already:

“We’ve already served billions of queries with our generative AI features. It’s enabling people to access new information, to ask questions in new ways, and to ask more complex questions.”

Google reports increased Search usage and user satisfaction among those interacting with the new AI overview results.

The company also highlighted its “Circle to Search” feature on Android, which allows users to circle objects on their screen or in videos to get instant AI-powered answers via Google Lens.

Reorganizing For The “Gemini Era”

As part of the AI roadmap, Alphabet is consolidating all teams building AI models under the Google DeepMind umbrella.

Pichai revealed that, through hardware and software improvements, the company has reduced machine costs associated with its generative AI search results by 80% over the past year.

He states:

“Our data centers are some of the most high-performing, secure, reliable and efficient in the world. We’ve developed new AI models and algorithms that are more than one hundred times more efficient than they were 18 months ago.

How Will Google Make Money With AI?

Alphabet sees opportunities to monetize AI through its advertising products, Cloud offerings, and subscription services.

Google is integrating Gemini into ad products like Performance Max. The company’s Cloud division is bringing “the best of Google AI” to enterprise customers worldwide.

Google One, the company’s subscription service, surpassed 100 million paid subscribers in Q1 and introduced a new premium plan featuring advanced generative AI capabilities powered by Gemini models.

Future Outlook

Pichai outlined six key advantages positioning Alphabet to lead the “next wave of AI innovation”:

Research leadership in AI breakthroughs like the multimodal Gemini model
Robust AI infrastructure and custom TPU chips
Integrating generative AI into Search to enhance the user experience
A global product footprint reaching billions
Streamlined teams and improved execution velocity
Multiple revenue streams to monetize AI through advertising and cloud

With upcoming events like Google I/O and Google Marketing Live, the company is expected to share further updates on its AI initiatives and product roadmap.

Featured Image: Sergei Elagin/Shutterstock