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Is RankBrain A Ranking Factor?

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Is RankBrain A Ranking Factor?

Without knowing what “RankBrain” means, people new to SEO may assume it refers to a technology Google uses to rank search results.

That assumption isn’t far off, but not every component of Google’s search algorithm is a ranking factor in and of itself.

In this article, we’ll investigate the claims around RankBrain as a ranking factor and provide clarity on what RankBrain is and how it’s used in search results.

The Claim: RankBrain Is A Ranking Factor

RankBrain is a technology that’s said to impact how Google returns search results.

Due to its association with search, RankBrain is commonly referred to as a ranking factor.

If you’re new to SEO, you may hear that and start to think RankBrain is one more signal you have to optimize for.

But that’s exactly not how it works.

The next section goes over what RankBrain is designed to do, and when it’s called upon by Google to assist with answering queries.

The Evidence: Is RankBrain A Ranking Factor?

RankBrain is an artificial intelligence (AI) system introduced in 2015 to help Google with returning results for queries that have never been searched before.

That changed somewhere between the spring of 2015 and 2016 when an unannounced update was made to RankBrain which integrated the AI into all queries.

This information was revealed in a Wired article, which notes Google isn’t clear on how RankBrain improves all queries but it does affect rankings.

From Wired:

“Google is characteristically fuzzy on exactly how it improves search (something to do with the long tail? Better interpretation of ambiguous requests?) but [Google engineer Jeff Dean] says that RankBrain is “involved in every query,” and affects the actual rankings “probably not in every query but in a lot of queries.”

What differentiates RankBrain from other Google algorithms is its ability to learn how to answer more ambiguous queries.

As Google’s Gary Illyes explains, this is accomplished through making educated guesses at what a user would likely click on for a never-before-seen query.

“RankBrain is a PR-sexy machine learning ranking component that uses historical search data to predict what would a user most likely click on for a previously unseen query.”

RankBrain allows Google to solve problems it used to run into with traditional algorithms.

Contrary to popular theories about how RankBrain works, it does not use data gathered from users’ interactions with a web page.

RankBrain relies more on data gathered from users’ interactions with search results.

Illyes provides further clarity:

“It is a really cool piece of engineering that saved our butts countless times whenever traditional algos were like, e.g. “oh look a “not” in the query string! let’s ignore the hell out of it!”, but it’s generally just relying on (sometimes) months old data about what happened on the results page itself, not on the landing page.”

In short – RankBrain is a machine learning system that allows Google’s search algorithm to deliver more relevant results.

This is thought to be accomplished through an improved understanding of ambiguous queries and long-tail keywords.

RankBrain uses data gathered from users’ interactions with search results to predict which pages will likely get clicked on for a brand new search query.

RankBrain As A Ranking Factor: Our Verdict

Google has confirmed that RankBrain is used to rank search results and it is involved in all queries.

In 2016, Andrey Lipattsev, a Google Search Quality Senior Strategist at Google, said RankBrain was one of the three most important ranking signals (along with content and links).

RankBrain continues to play an important role in search results today.

RankBrain differs from traditional ranking factors in that there’s not an obvious way to actively optimize for it.

How do you optimize for ambiguous keywords or queries that no one’s ever entered into Google before?

The only option is to provide Google with as much information about a page as possible, which is something site owners should be doing anyway if they’re creating holistic content for users.

Illyes was asked this question once and replied with a similar sentiment:

“you optimize your content for users and thus for RankBrain. That hasn’t changed.”

Search Engine Journal VIP Contributor Dave Davies provides more advanced tips for communicating information to Google regarding different entities on a page in A Complete Guide to the Google RankBrain Algorithm.


Featured Image: Robin Biong/Search Engine Journal




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Google Cautions On Blocking GoogleOther Bot

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Google cautions about blocking and opting out of getting crawled by the GoogleOther crawler

Google’s Gary Illyes answered a question about the non-search features that the GoogleOther crawler supports, then added a caution about the consequences of blocking GoogleOther.

What Is GoogleOther?

GoogleOther is a generic crawler created by Google for the various purposes that fall outside of those of bots that specialize for Search, Ads, Video, Images, News, Desktop and Mobile. It can be used by internal teams at Google for research and development in relation to various products.

The official description of GoogleOther is:

“GoogleOther is the generic crawler that may be used by various product teams for fetching publicly accessible content from sites. For example, it may be used for one-off crawls for internal research and development.”

Something that may be surprising is that there are actually three kinds of GoogleOther crawlers.

Three Kinds Of GoogleOther Crawlers

  1. GoogleOther
    Generic crawler for public URLs
  2. GoogleOther-Image
    Optimized to crawl public image URLs
  3. GoogleOther-Video
    Optimized to crawl public video URLs

All three GoogleOther crawlers can be used for research and development purposes. That’s just one purpose that Google publicly acknowledges that all three versions of GoogleOther could be used for.

What Non-Search Features Does GoogleOther Support?

Google doesn’t say what specific non-search features GoogleOther supports, probably because it doesn’t really “support” a specific feature. It exists for research and development crawling which could be in support of a new product or an improvement in a current product, it’s a highly open and generic purpose.

This is the question asked that Gary narrated:

“What non-search features does GoogleOther crawling support?”

Gary Illyes answered:

“This is a very topical question, and I think it is a very good question. Besides what’s in the public I don’t have more to share.

GoogleOther is the generic crawler that may be used by various product teams for fetching publicly accessible content from sites. For example, it may be used for one-off crawls for internal research and development.

Historically Googlebot was used for this, but that kind of makes things murky and less transparent, so we launched GoogleOther so you have better controls over what your site is crawled for.

That said GoogleOther is not tied to a single product, so opting out of GoogleOther crawling might affect a wide range of things across the Google universe; alas, not Search, search is only Googlebot.”

It Might Affect A Wide Range Of Things

Gary is clear that blocking GoogleOther wouldn’t have an affect on Google Search because Googlebot is the crawler used for indexing content. So if blocking any of the three versions of GoogleOther is something a site owner wants to do, then it should be okay to do that without a negative effect on search rankings.

But Gary also cautioned about the outcome that blocking GoogleOther, saying that it would have an effect on other products and services across Google. He didn’t state which other products it could affect nor did he elaborate on the pros or cons of blocking GoogleOther.

Pros And Cons Of Blocking GoogleOther

Whether or not to block GoogleOther doesn’t necessarily have a straightforward answer. There are several considerations to whether doing that makes sense.

Pros

Inclusion in research for a future Google product that’s related to search (maps, shopping, images, a new feature in search) could be useful. It might be helpful to have a site included in that kind of research because it might be used for testing something good for a site and be one of the few sites chosen to test a feature that could increase earnings for a site.

Another consideration is that blocking GoogleOther to save on server resources is not necessarily a valid reason because GoogleOther doesn’t seem to crawl so often that it makes a noticeable impact.

If blocking Google from using site content for AI is a concern then blocking GoogleOther will have no impact on that at all. GoogleOther has nothing to do with crawling for Google Gemini apps or Vertex AI, including any future products that will be used for training associated language models. The bot for that specific use case is Google-Extended.

Cons

On the other hand it might not be helpful to allow GoogleOther if it’s being used to test something related to fighting spam and there’s something the site has to hide.

It’s possible that a site owner might not want to participate if GoogleOther comes crawling for market research or for training machine learning models (for internal purposes) that are unrelated to public-facing products like Gemini and Vertex.

Allowing GoogleOther to crawl a site for unknown purposes is like giving Google a blank check to use your site data in any way they see fit outside of training public-facing LLMs or purposes related to named bots like GoogleBot.

Takeaway

Should you block GoogleOther? It’s a coin toss. There are possible potential benefits but in general there isn’t enough information to make an informed decision.

Listen to the Google SEO Office Hours podcast at the 1:30 minute mark:

Featured Image by Shutterstock/Cast Of Thousands

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AI Search Boosts User Satisfaction

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AI chat robot on search engine bar. Artificial intelligence bot innovation technology answer question with smart solution. 3D vector created from graphic software.

A new study finds that despite concerns about AI in online services, users are more satisfied with search engines and social media platforms than before.

The American Customer Satisfaction Index (ACSI) conducted its annual survey of search and social media users, finding that satisfaction has either held steady or improved.

This comes at a time when major tech companies are heavily investing in AI to enhance their services.

Search Engine Satisfaction Holds Strong

Google, Bing, and other search engines have rapidly integrated AI features into their platforms over the past year. While critics have raised concerns about potential negative impacts, the ACSI study suggests users are responding positively.

Google maintains its position as the most satisfying search engine with an ACSI score of 81, up 1% from last year. Users particularly appreciate its AI-powered features.

Interestingly, Bing and Yahoo! have seen notable improvements in user satisfaction, notching 3% gains to reach scores of 77 and 76, respectively. These are their highest ACSI scores in over a decade, likely due to their AI enhancements launched in 2023.

The study hints at the potential of new AI-enabled search functionality to drive further improvements in the customer experience. Bing has seen its market share improve by small but notable margins, rising from 6.35% in the first quarter of 2023 to 7.87% in Q1 2024.

Customer Experience Improvements

The ACSI study shows improvements across nearly all benchmarks of the customer experience for search engines. Notable areas of improvement include:

  • Ease of navigation
  • Ease of using the site on different devices
  • Loading speed performance and reliability
  • Variety of services and information
  • Freshness of content

These improvements suggest that AI enhancements positively impact various aspects of the search experience.

Social Media Sees Modest Gains

For the third year in a row, user satisfaction with social media platforms is on the rise, increasing 1% to an ACSI score of 74.

TikTok has emerged as the new industry leader among major sites, edging past YouTube with a score of 78. This underscores the platform’s effective use of AI-driven content recommendations.

Meta’s Facebook and Instagram have also seen significant improvements in user satisfaction, showing 3-point gains. While Facebook remains near the bottom of the industry at 69, Instagram’s score of 76 puts it within striking distance of the leaders.

Challenges Remain

Despite improvements, the study highlights ongoing privacy and advertising challenges for search engines and social media platforms. Privacy ratings for search engines remain relatively low but steady at 79, while social media platforms score even lower at 73.

Advertising experiences emerge as a key differentiator between higher- and lower-satisfaction brands, particularly in social media. New ACSI benchmarks reveal user concerns about advertising content’s trustworthiness and personal relevance.

Why This Matters For SEO Professionals

This study provides an independent perspective on how users are responding to the AI push in online services. For SEO professionals, these findings suggest that:

  1. AI-enhanced search features resonate with users, potentially changing search behavior and expectations.
  2. The improving satisfaction with alternative search engines like Bing may lead to a more diverse search landscape.
  3. The continued importance of factors like content freshness and site performance in user satisfaction aligns with long-standing SEO best practices.

As AI becomes more integrated into our online experiences, SEO strategies may need to adapt to changing user preferences.


Featured Image: kate3155/Shutterstock

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Google To Upgrade All Retailers To New Merchant Center By September

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Google To Upgrade All Retailers To New Merchant Center By September

Google has announced plans to transition all retailers to its updated Merchant Center platform by September.

This move will affect e-commerce businesses globally and comes ahead of the holiday shopping season.

The Merchant Center is a tool for online retailers to manage how their products appear across Google’s shopping services.

Key Changes & Features

The new Merchant Center includes several significant updates.

Product Studio

An AI-powered tool for content creation. Google reports that 80% of current users view it as improving efficiency.

This feature allows retailers to generate tailored product assets, animate still images, and modify existing product images to match brand aesthetics.

It also simplifies tasks like background removal and image resolution enhancement.

Centralized Analytics

A new tab consolidating various business insights, including pricing data and competitive analysis tools.

Retailers can access pricing recommendations, competitive visibility reports, and retail-specific search trends, enabling them to make data-driven decisions and capitalize on popular product categories.

Redesigned Navigation

Google claims the new interface is more intuitive and cites increased setup success rates for new merchants.

The platform now offers simplified website verification processes and can pre-populate product information during setup.

Initial User Response

According to Google, early adopters have shown increased engagement with the platform.

The company reports a 25% increase in omnichannel merchants adding product offers in the new system. However, these figures have yet to be independently verified.

Jeff Harrell, Google’s Senior Director of Merchant Shopping, states in an announcement:

“We’ve seen a significant increase in retention and engagement among existing online merchants who have moved to the new Merchant Center.”

Potential Challenges and Support

While Google emphasizes the upgrade’s benefits, some retailers, particularly those comfortable with the current version, may face challenges adapting to the new system.

The upgrade’s mandatory nature could raise concerns among users who prefer the existing interface or have integrated workflows based on the current system.

To address these concerns, Google has stated that it will provide resources and support to help with the transition. This includes tutorial videos, detailed documentation, and access to customer support teams for troubleshooting.

Industry Context

This update comes as e-commerce platforms evolve, with major players like Amazon and Shopify enhancing their seller tools. Google’s move is part of broader efforts to maintain competitiveness in the e-commerce services sector.

The upgrade could impact consumers by improving product listings and providing more accurate information across Google’s shopping services.

For the e-commerce industry as a whole, it signals a continued push towards AI-driven tools and data-centric decision-making.

Transition Timeline

Google states that retailers will be automatically upgraded by September if they still need to transition.

The company advises users to familiarize themselves with the new features before the busy holiday shopping period.


Featured Image: BestForBest/Shutterstock

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