Tag Archive for: Google Algorithm

What is Google E-E-A-T?

Have you ever considered how Google ranks and displays websites? One key factor is the E-E-A-T principle. This acronym holds significant power over the future of websites, determining their visibility in the vast online landscape. But what exactly does E-E-A-T entail, and why does it matter? 

With the rise of AI-generated content, simply spinning up authority sites and bombarding them with links might not cut it anymore, at least not as a long-term strategy. Google E-E-A-T is a framework that Google uses to evaluate the quality of content on websites. E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness. This is a part of Google’s search quality rater guidelines, a handbook that Google uses to weigh the quality and credibility of a website’s content. 

Join us as we discuss the importance of this concept, exploring its profound impact on Search Engine Optimization (SEO). Here’s everything you need to know.

Understanding Google’s Quality Standards

Google published its search quality evaluator guidelines back in 2013, making them accessible to all marketers. These standards demonstrate how Google assesses web pages and ranks content from high to low quality. So, what do Google’s quality standards mean for us marketers who handle SEO? The overall goal of this is to help ensure that the page is created to help users. Here are a few examples of what a high-quality “user-centered” web page should look like:

  • Sharing information about a specific topic.
  • Sharing personal/social information.
  • Sharing photos, videos, and other media.
  • Expressing opinions or points of view.
  • Entertaining users.
  • Selling products or services.

Adhering to Google’s quality standards is crucial for enhancing user experience. Your site and content should have a user-focused purpose that provides real benefits. Now, let’s explore the extra “E” in ‘E-E-A-T,’ which stands for Expertise, Authoritativeness, Trustworthiness, and the new addition: Experience.

What is E-E-A-T?

As discussed, E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness. It’s a framework used by Google’s algorithms to evaluate the quality and credibility of your company’s online information. In a nutshell, if your website’s user experience is subpar and doesn’t seem to be a trustworthy source, Google may view your site as unreliable and limit your ability to rank — even if you’re following all other “best practice” SEO guidance. 

Topics that require high E-E-A-T include medical advice, journalism/news stories, and financial, legal, and tax advice. A common misconception is that E-E-A-T is a direct ranking factor. It isn’t. Instead, it indirectly affects the algorithm because search quality raters evaluate sites for it.

Let’s break down each component for a closer look at what each entails:

Experience: This dimension assesses the depth and breadth of a website’s experience within its niche. It considers factors such as the website’s longevity, the frequency of updates, and the richness of user interactions.

Expertise: Expertise revolves around the proficiency and knowledge demonstrated by content creators. Google seeks content that showcases a deep understanding of the subject matter, providing users with valuable insights and solutions.

Authoritativeness: Authoritativeness measures the reputation of the content creator and the website hosting the content. It considers factors like backlinks, mentions from other reputable sources, and the overall prestige of the website within its niche.

Trustworthiness: Trustworthiness assesses the reliability and integrity of the content. It looks at factors such as transparency, citing credible sources, and maintaining high accuracy and truthfulness.

Why Does E-E-A-T Matter for SEO?

Google’s primary goal is to provide users with the most valuable and reliable information in response to their queries. By evaluating content based on this set of criteria, Google can prioritize high-quality content while filtering out low-quality or misleading information. Here’s how it influences SEO:

  1. Higher Rankings: Websites that demonstrate expertise, authoritativeness, and trustworthiness are more likely to rank higher in search results. This is because Google perceives them as reliable information sources worth showcasing to users.
  2. Enhanced Visibility: When your website meets Google’s E-E-A-T criteria, it’s more likely to be featured in Google’s Knowledge Graph, Knowledge Panels, and other prominent search features. This increased visibility can drive more organic traffic to your site.
  3. Credibility and Reputation: Building and maintaining E-E-A-T improves your search rankings and helps enhance your brand’s credibility and reputation. Users are more likely to trust and engage with content from sources they perceive as authoritative and trustworthy.
  4. Long-Term Sustainability: E-E-A-T is not a short-term SEO tactic; it’s a long-term strategy for sustainable growth. By consistently producing high-quality content that aligns with E-E-A-T principles, you can establish your website as a reputable authority in your industry.

How to Improve E-E-A-T for Your Website

Now that we grasp the significance of E-E-A-T for SEO let’s delve into strategies to enhance it for your site:

  1. Invest in Content Quality: Focus on creating comprehensive, well-researched, and authoritative content that addresses the needs and interests of your target audience.
  2. Showcase Expertise: Highlight the expertise of your content by showcasing their credentials, certifications, and relevant experience. Establishing yourself as a thought leader in your industry can significantly boost your E-E-A-T.
  3. Build Authoritative Backlinks: Earn backlinks from reputable websites within your niche. This helps improve your website’s authority and signals that other trusted sources vouch for your content to Google.
  4. Prioritize User Experience: A user-friendly website design, fast loading times, and clear navigation contribute to a positive user experience, which in turn helps enhance trustworthiness.
  5. Be Transparent and Credible: Disclose your sources, provide accurate information, and avoid misleading or deceptive practices. Transparency and honesty are essential for helping build trust with your audience.

Last Thoughts

Google’s E-E-A-T principle helps shape search engine rankings and affects user trust and engagement. You can enhance your credibility and long-term success in the digital landscape by prioritizing experience, expertise, authoritativeness, and trustworthiness in your content creation and SEO strategies.

It’s crucial to have a sound digital marketing strategy in place. Understanding your audience and their needs can attract more traffic and drive conversions. It’s important to remember that quality content is not a one-time effort but an ongoing research, refinement, and optimization process.

As a Google Partner, Onimod Global has the experience to help you with your SEO, social media marketing and advertising, and content creation needs. Whether you have questions about creating quality content or want to learn more about our services, we are here to help.

Contact us today to speak with our digital marketing team and learn how we can help you achieve your 2024 digital marketing goals.

3 Crucial SEO Tips for 2021

Search engine optimization, SEO, by definition is: a strategy in digital marketing which aims to improve your ranking on search engines.

Sounds easy to conquer, but we all know it isn’t so simple. It’s extremely difficult to keep up with Google’s 500-600 algorithm updates annually. That means there is at least one update per day every year. Experts who dedicate their careers to unlocking the secret to search engine ranking optimization still are puzzled at the end of the day. Fear not, we are here to help guide you with the top 3 SEO tips for 2021 that will get you on the right track to ranking success.

1. Understand your website’s core vitals

Maybe you’ve never heard the phrase before, but the philosophy behind it is becoming more crucial to your SEO and ranking. In May of 2022, Google will roll out Page Experience, which is a brand new algorithm ranking pages based off of their “core web vital” scores. A brief overview of what to look out for here is: 

Largest Contentful Paint (LCP) – Measures page speed. This is the time it takes for a page’s main content to load. The ideal LCP is 2.5 seconds or faster.

First Input Delay (FID) – Measures page responsiveness. This is the time it takes for a page to become interactive. The ideal FID is less than 100 ms. 

Cumulative Layout Shift (CLS) – Measures visual stability. This is the amount of unexpected layout shift of visual page content. The ideal CLS is less than .1.

2. Focus on featured snippets
If they aren’t already, featured snippets should be a priority to include in your SEO strategy for 2021. Also commonly referred to as the holy grail of search, featured snippets appear at the very top of search engine page results (SERP), or in position zero, in a rectangular box. You can’t technically “select” the content shown in a featured snippet, but you can optimize your content so it’s more likely to appear in a featured snippet. Here are a few recommendations.

Use questions: all content that you write needs to be composed with the user in mind. What would they search in Google in order to come across your content?

Long term keywords: the longer words in a search query, the higher chance it will return a featured snippet. Only 4.3% of single word keywords resulted in a featured snippet as compared to 17% of keywords made up of 5 words, and 55.5% of keywords made of 10 words.
Keep formats in mind: When it comes to featured snippets, there are four different formats: paragraph, list, table and video. While writing your content with the goal of achieving a featured snippet, keep these different formats in mind. Also remember, Google wants to display information easily and distinctly to searchers looking for a fast answer. So format for the speed reader.

3. Focus on user experience
In 2021, user experience is more important than ever in terms of SEO. As mentioned in tip #1, the new focus on core web vitals is all about user experience. In addition to that, Google also takes into account bounce rate, dwell time, and click-through percentage. The goal is to have a user click on your result, spend time clicking on different pages, and spend at least 3 minutes on your site.

More From Onimod Global

As certified SEO experts, our team is here to assist your business with holistic digital marketing strategies including SEO, because our goal is to make you more sucessful. To get in contact for an audit on your digital presence, get in touch with us here.

Top 5 Most Important Google Algorithm Updates

Almost every day, Google introduces changes to its ranking algorithm. They even claim to update their search algorithm several thousand times per year. Some are tiny tweaks, usually too small to notice. But, every once in a while, Google introduces a change so fundamental, that it completely alters the way we do SEO forever.

#1. Panda

Hazards: Duplicate, plagiarized or thin content; user-generated spam; keyword stuffing.

How does it work? Panda assigns a “quality score” to webpages; this score is then used as a ranking factor. Initially, Panda was a filter rather than part of Google’s ranking algorithm. In January 2016, it was officially incorporated into the core algorithm. Panda rollouts have become more frequent, so both penalties and recoveries now happen faster.

#2. Penguin

Hazards: Spammy or irrelevant links; links with over-optimized anchor text

How it works: Google Penguin’s objective is to down-rank sites whose backlinks look unnatural. This update put an end to low-effort link building, like buying links from link farms and PBNs.

#3. Hummingbird

Hazards: Keyword stuffing; low quality content

How it works: The Hummingbird algorithm helps Google to better interpret search queries and provide results that actually what the search was intended for (as opposed to the individual terms within the query). While keywords still remain very important, the Hummingbird algorithm makes it possible for a page to rank for a query even if it doesn’t contain the exact words the searcher entered. According to Search Engine Land, his is achieved through the natural language processing that relies on latent semantic indexing, co-occurring terms and synonyms.

#4. Pigeon

Hazards: Poor on- and off-page SEO

How it works: Pigeon affects those searches in which the user’s location plays an important part. The update created closer ties between the local algorithm and the core algorithm: traditional SEO factors are now used to rank local results.

#5 Mobile

Hazards: Lack of a mobile version of the page; poor mobile usability.

How it works: This, and subsequent mobile search updates (2018, 2020) have shifted the focus from a desktop to a mobile version of your website. Today, Google ranks all websites based on how fast and user-friendly their mobile versions are. This automatically puts you at a huge advantage compared to competitors. The faster the content is mobile optimized, the higher Google will prioritize your ad.

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What Google’s Algorithm Adjustment Means for Digital Marketing

Nearly every digital marketer in today’s society utilizes Google as a primary form of advertisement. With more than 6.5 billion searches being made each day, the need to rank well on Google’s search results page is imperative.

Whether you are optimizing a website to rank well on its own, or spending a few dollars through Google AdWords, the changes coming to Google’s algorithm will have a significant effect on those advertising efforts.

Most Recent Update

Google continually updates its algorithm to show the most relevant results to users as possible. The latest update arrived on August 19th.

There is never one single cause of an algorithm adjustment. Instead, the adjustment is meant to target many different areas in order to improve overall quality of the search results displayed by Google.

Glenn Gabe, columnist for Search Engine Land and Search Engine Watch, investigated the algorithm change and gave his opinions on how he thought it would affect marketers. According to Gabe, Google advertisers should avoid:

  • Use of Deceptive Advertising: deploying deceptive, aggressive, or disruptive advertising can be detrimental to a site’s quality. Instead, gear your site toward the user and their needs. Do not bombard them with full-screen ads and site redirects.
  • Broken User Interface Elements: We have all had an experience where we click on a link and receive some sort of “404 error: Page Not Found” message. Make sure that your site works properly and does not contain any of these pesky UI flaws.
  • Low Query-Based Relevance: This element should be obvious. If a search term does not apply to your site, then it should not be ranking well for that term. Google’s goal is to provide the user with exactly what they are looking for. If your site isn’t helpful to the user, then it’s as good as gone from the top search results list.

Gabe suggests using the following methods to improve advertisements in the wake of the algorithm update:

  • Category (Tag-like) Pages: WordPress sites often include the option of adding a category and various tag to each page. Gabe noticed that even some sites that showed an overall downward trend since the algorithm update still had positive numbers to report for these category pages.
  • Full, Quality Content: Try to fill your site with all of the best information possible. This does not mean that you need to write pages and pages of content, it just means that you need to clearly state what you can do for the consumer and why you can do it best.
  • Open User Experience: Allowing users to add their own comments to content on your site is a great way to add value. This may be in the form of a review or an actual comment on a certain post or news article.

Location Improvements

Google has also shown an increased interest in the prominence of local businesses on their search results page. After all, a restaurant located in New York City will prove of little use to a young woman in Seattle looking for a bit to eat after work.

As Google begins to favor local establishments, it becomes more and more important for all kinds of businesses to make sure that their location is conveniently and correctly displayed across various platforms. For example, you will want to make sure that the address you have listed on Facebook perfectly matches the one listed on Yelp.

Evaluate Your Business Today!

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Google rolls out similar audiences for Search and Shopping

Now out of beta, similar audiences for Search enables advertisers to target users searching for the same kinds of things as recent site visitors. Read more

Google Says it Has Now Tracked 4 Billion Store Visits From Ads

Onimod Global shares how the company says thousands more advertisers will gain access to store visits data as a result of improved measurement techniques and machine learning-powered modeling. Read more

Google Search Algorithm Update February 7th

We just had some Google algorithm update a week ago potentially targeting spammy links I believe. And now a week later, around February 7th, yesterday, it seems there was another algorithm update. This update doesn’t seem specific to links or spam but rather just a normal unconfirmed Google update where ranking changes shift based on something changing at Google.

I do not believe it is related to the mobile bug because most of the automated tracking tools only track desktop search.

There is some chatter, the chatter in the SEO community is not YET that hot but it might heat up throughout the day as people check their analytics and tools.

An ongoing WebmasterWorld thread has these posts:

SERPs movements again in our vertical. We’re seeing some recoveries from previous penguin casualties and some domain crowding. Spam STILL having a huge positive impact.

Yesterday (Tue 7th) I saw a huge spike in organic traffic, ~30% over avg, and 18% increase from previous record day in November. It’s a Canadian financial-related site. Increases from both Google.ca as well as other search engines/

Here is a post on Twitter that even caught Gary Illyes attention:

Screen Shot 02-08-17 at 01.51 PM

 

And here are the tracking tools showing changes on the 7th, note Mozcast is well behind in terms of tracking so this might be related to the link spam update we covered last week?

Mozcast:

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SERP Metrics:

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Algoroo:

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Accuranker:

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RankRanger:

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Have you noticed any changes over the past 24 hours?

 

 

 

HT SE Roundtable

Official Google Webmaster Central Blog – Penguin is now part of our core algorithm

Google’s algorithms rely on more than 200 unique signals or “clues” that make it possible to surface what you might be looking for. These signals include things like the specific words that appear on websites, the freshness of content, your region and PageRank. One specific signal of the algorithms is called Penguin, which was first launched in 2012 and today has an update.

After a period of development and testing, Google are now rolling out an update to the Penguin algorithm in all languages. Here are the key changes you’ll see, which were also among webmasters’ top requests to them:

  • Penguin is now real-time. Historically, the list of sites affected by Penguin was periodically refreshed at the same time. Once a webmaster considerably improved their site and its presence on the internet, many of Google’s algorithms would take that into consideration very fast, but others, like Penguin, needed to be refreshed. With this change, Penguin’s data is refreshed in real time, so changes will be visible much faster, typically taking effect shortly after we recrawl and reindex a page. It also means Google aren’t going to comment on future refreshes.
  • Penguin is now more granular. Penguin now devalues spam by adjusting ranking based on spam signals, rather than affecting ranking of the whole site.

The web has significantly changed over the years, but webmasters should be free to focus on creating amazing, compelling websites. It’s also important to remember that updates like Penguin are just one of more than 200 signals Google use to determine rank.

For more information on the above changes and how it benefits you, contact an Onimod Global Digital Marketing expert today.

All About the New Google RankBrain Algorithm

Yesterday, news emerged that Google was using a machine-learning artificial intelligence system called “RankBrain” to help sort through its search results. Wondering how that works and fits in with Google’s overall ranking system? Here’s what we know about RankBrain.

The information covered below comes from three original sources and has been updated over time, with notes where updates have happened. Here are those sources:

First is the Bloomberg story that broke the news about RankBrain yesterday. Second, additional information that Google has now provided directly to Search Engine Land. Third, our own knowledge and best assumptions in places where Google isn’t providing answers. We’ll make clear where these sources are used, when deemed necessary, apart from general background information.

What is RankBrain?

RankBrain is Google’s name for a machine-learning artificial intelligence system that’s used to help process its search results, as was reported by Bloomberg and also confirmed to us by Google.

What is machine learning?

Machine learning is where a computer teaches itself how to do something, rather than being taught by humans or following detailed programming.

What is artificial intelligence?

True artificial intelligence, or AI for short, is where a computer can be as smart as a human being, at least in the sense of acquiring knowledge both from being taught and from building on what it knows and making new connections.

True AI exists only in science fiction novels, of course. In practice, AI is used to refer to computer systems that are designed to learn and make connections.

How’s AI different from machine learning? In terms of RankBrain, it seems to us they’re fairly synonymous. You may hear them both used interchangeably, or you may hear machine learning used to describe the type of artificial intelligence approach being employed.

So RankBrain is the new way Google ranks search results?

No. RankBrain is part of Google’s overall search “algorithm,” a computer program that’s used to sort through the billions of pages it knows about and find the ones deemed most relevant for particular queries.

What’s the name of Google’s search algorithm?

http://searchengineland.com/figz/wp-content/seloads/2014/08/google-hummingbird1-ss-1920-800x450.jpg

It’s called Hummingbird, as we reported in the past. For years, the overall algorithm didn’t have a formal name. But in the middle of 2013, Google overhauled that algorithm and gave it a name, Hummingbird.

So RankBrain is part of Google’s Hummingbird search algorithm?

That’s our understanding. Hummingbird is the overall search algorithm, just like a car has an overall engine in it. The engine itself may be made up of various parts, such as an oil filter, a fuel pump, a radiator and so on. In the same way, Hummingbird encompasses various parts, with RankBrain being one of the newest.

In particular, we know RankBrain is part of the overall Hummingbird algorithm because the Bloomberg article makes clear that RankBrain doesn’t handle all searches, as only the overall algorithm would.

Hummingbird also contains other parts with names familiar to those in the SEO space, such as Panda, Penguin and Payday designed to fight spam, Pigeon designed to improve local results, Top Heavy designed to demote ad-heavy pages, Mobile Friendly designed to reward mobile-friendly pages and Pirate designed to fight copyright infringement.

I thought the Google algorithm was called “PageRank”

PageRank is part of the overall Hummingbird algorithm that covers a specific way of giving pages credit based on the links from other pages pointing at them.

PageRank is special because it’s the first name that Google ever gave to one of the parts of its ranking algorithm, way back at the time the search engine began, in 1998.

What about these “signals” that Google uses for ranking?

Signals are things Google uses to help determine how to rank webpages. For example, it will read the words on a webpage, so words are a signal. If some words are in bold, that might be another signal that’s noted. The calculations used as part of PageRank give a page a PageRank score that’s used as a signal. If a page is noted as being mobile-friendly, that’s another signal that’s registered.

All these signals get processed by various parts within the Hummingbird algorithm to figure out which pages Google shows in response to various searches.

How many signals are there?

Google has fairly consistently spoken of having more than 200 major ranking signals that are evaluated that, in turn, might have up to 10,000 variations or sub-signals. It more typically just says “hundreds” of factors, as it did in yesterday’s Bloomberg article.

If you want a more visual guide to ranking signals, see our Periodic Table Of SEO Success Factors:

http://searchengineland.com/figz/wp-content/seloads/2015/06/periodic-table-of-seo-2015-800x548.jpg

It’s a pretty good guide, we think, to general things that search engines like Google use to help rank webpages.

And RankBrain is the third-most important signal?

That’s right. From out of nowhere, this new system has become what Google says is the third-most important factor for ranking webpages. From the Bloomberg article:

RankBrain is one of the “hundreds” of signals that go into an algorithm that determines what results appear on a Google search page and where they are ranked, Corrado said. In the few months it has been deployed, RankBrain has become the third-most important signal contributing to the result of a search query, he said.

What are the first- and second-most important signals?

When this story was originally written, Google wouldn’t tell us. Our assumption was this:

My personal guess is that links remain the most important signal, the way that Google counts up those links in the form of votes. It’s also a terribly aging system, as I’ve covered in my Links: The Broken “Ballot Box” Used By Google & Bing article from the past.

As for the second-most important signal, I’d guess that would be “words,” where words would encompass everything from the words on the page to how Google’s interpreting the words people enter into the search box outside of RankBrain analysis.

That turned out to be pretty much right.

What exactly does RankBrain do?

From emailing with Google, I gather RankBrain is mainly used as a way to interpret the searches that people submit to find pages that might not have the exact words that were searched for.

Didn’t Google already have ways to find pages beyond the exact query entered?

Yes, Google has found pages beyond the exact terms someone enters for a very long time. For example, years and years ago, if you’d entered something like “shoe,” Google might not have found pages that said “shoes,” because those are technically two different words. But “stemming” allowed Google to get smarter, to understand that shoes is a variation of shoe, just like “running” is a variation of “run.”

Google also got synonym smarts, so that if you searched for “sneakers,” it might understand that you also meant “running shoes.” It even gained some conceptual smarts, to understand that there are pages about “Apple” the technology company versus “apple” the fruit.

What about the Knowledge Graph?

The Knowledge Graph, launched in 2012, was a way that Google grew even smarter about connections between words. More important, it learned how to search for “things not strings,” as Google has described it.

Strings means searching just for strings of letters, such as pages that match the spelling of “Obama.” Things means that instead, Google understands when someone searches for “Obama,” they probably mean US President Barack Obama, an actual person with connections to other people, places and things.

The Knowledge Graph is a database of facts about things in the world and the relationships between them. It’s why you can do a search like “when was the wife of obama born” and get an answer about Michele Obama as below, without ever using her name:

http://searchengineland.com/figz/wp-content/seloads/2015/10/when_was_the_wife_of_obama_born_-_Google_Search-800x573.png

How’s RankBrain helping refine queries?

The methods Google already uses to refine queries generally all flow back to some human being somewhere doing work, either having created stemming lists or synonym lists or making database connections between things. Sure, there’s some automation involved. But largely, it depends on human work.

The problem is that Google processes three billion searches per day. In 2007, Google said that 20 percent to 25 percent of those queries had never been seen before. In 2013, it brought that number down to 15 percent, which was used again in yesterday’s Bloomberg article and which Google reconfirmed to us. But 15 percent of three billion is still a huge number of queries never entered by any human searcher — 450 million per day.

Among those can be complex, multi-word queries, also called “long-tail” queries. RankBrain is designed to help better interpret those queries and effectively translate them, behind the scenes in a way, to find the best pages for the searcher.

As Google told us, it can see patterns between seemingly unconnected complex searches to understand how they’re actually similar to each other. This learning, in turn, allows it to better understand future complex searches and whether they’re related to particular topics. Most important, from what Google told us, it can then associate these groups of searches with results that it thinks searchers will like the most.

Google didn’t provide examples of groups of searches or give details on how RankBrain guesses at what are the best pages. But the latter is probably because if it can translate an ambiguous search into something more specific, it can then bring back better answers.

How about an example?

While Google didn’t give groups of searches, the Bloomberg article did have a single example of a search where RankBrain is supposedly helping. Here it is:

What’s the title of the consumer at the highest level of a food chain

To a layperson like myself, “consumer” sounds like a reference to someone who buys something. However, it’s also a scientific term for something that consumes food. There are also levels of consumers in a food chain. That consumer at the highest level? The title — the name — is “predator.”

Entering that query into Google provides good answers, even though the query itself sounds pretty odd:

http://searchengineland.com/figz/wp-content/seloads/2015/10/What%E2%80%99s_the_title_of_the_consumer_at_the_highest_level_of_a_food_chain_-_Google_Search-794x600.png

Now consider how similar the results are for a search like “top level of the food chain,” as shown below:

http://searchengineland.com/figz/wp-content/seloads/2015/10/top_level_of_the_food_chain_-_Google_Search-594x600.png

Imagine that RankBrain is connecting that original long and complicated query to this much shorter one, which is probably more commonly done. It understands that they are very similar. As a result, Google can leverage all it knows about getting answers for the more common query to help improve what it provides for the uncommon one.

Let me stress that I don’t know that RankBrain is connecting these two searches. I only know that Google gave the first example. This is simply an illustration of how RankBrain my be used to connect an uncommon search to a common one as a way of improving things.

Can Bing do this, too, with RankNet?

Back in 2005, Microsoft starting using its own machine-learning system, called RankNet, as part of what became its Bing search engine of today. In fact, the chief researcher and creator of RankNet was recently honored. But over the years, Microsoft has barely talked about RankNet.

You can bet that will likely change. It’s also interesting that when I put the search above into Bing, given as an example of how great Google’s RankBrain is, Bing gave me good results, including one listing that Google also returned:

http://searchengineland.com/figz/wp-content/seloads/2015/10/What%E2%80%99s_the_title_of_the_consumer_at_the_highest_level_of_a_food_chain_-_Bing-800x585.png

One query doesn’t mean that Bing’s RankNet is as good as Google’s RankBrain or vice versa. Unfortunately, it’s really difficult to come up with a list to do this type of comparison.

Any more examples?

Google did give us one fresh example: “How many tablespoons in a cup?” Google said that RankBrain favored different results in Australia versus the United States for that query because the measurements in each country are different, despite the similar names.

I tried to test this by searching at Google.com versus Google Australia. I didn’t see much difference, myself. Even without RankBrain, the results would often be different in this way just because of the “old-fashioned” means of favoring pages from known Australian sites for those searchers using Google Australia.

Does RankBrain really help?

Despite my two examples above being less than compelling as testimony to the greatness of RankBrain, I really do believe that it probably is making a big impact, as Google is claiming. The company is fairly conservative with what goes into its ranking algorithm. It does small tests all the time. But it only launches big changes when it has a great degree of confidence.

Integrating RankBrain, to the degree that it’s supposedly the third-most important signal, is a huge change. It’s not one that I think Google would do unless it really believed it was helping.

When Did RankBrain start?

Google told us that there was a gradual rollout of RankBrain in early 2015 and that it’s been fully live and global for a few months now.

What queries are impacted?

In October 2015, Google told Bloomberg that a “very large fraction” of the 15 percent of queries it normally never sees before were processed by RankBrain. In short, 15 percent or less.

In June 2016, news emerged that RankBrain was being used for every query that Google handles. See our story about that:

Is RankBrain always learning?

All learning that RankBrain does is offline, Google told us. It’s given batches of historical searches and learns to make predictions from these.

Those predictions are tested, and if proven good, then the latest version of RankBrain goes live. Then the learn-offline-and-test cycle is repeated.

Does RankBrain do more than query refinement?

Typically, how a query is refined — be it through stemming, synonyms or now RankBrain — has not been considered a ranking factor or signal.

Signals are typically factors that are tied to content, such as the words on a page, the links pointing at a page, whether a page is on a secure server and so on. They can also be tied to a user, such as where a searcher is located or their search and browsing history.

So when Google talks about RankBrain as the third-most important signal, does it really mean as a ranking signal? Yes. Google reconfirmed to us that there is a component where RankBrain is directly contributing somehow to whether a page ranks.

How exactly? Is there some type of “RankBrain score” that might assess quality? Perhaps, but it seems much more likely that RankBrain is somehow helping Google better classify pages based on the content they contain. RankBrain might be able to better summarize what a page is about than Google’s existing systems have done.

Or not. Google isn’t saying anything other than there’s a ranking component involved.

How do I learn more about RankBrain?

Google told us people who want to learn about word “vectors” — the way words and phrases can be mathematically connected — should check out this blog post, which talks about how the system (which wasn’t named RankBrain in the post) learned the concept of capital cities of countries just by scanning news articles:

http://searchengineland.com/figz/wp-content/seloads/2015/10/image00-800x593.gif

There’s a longer research paper this is based on here. You can even play with your own machine learning project using Google’s word2vec tool. In addition, Google has an entire area with its AI and machine learning papers, as does Microsoft.

 

H/T: Search Engine Land.