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December 6th, 2019, Posted by Pixel Global

Google RankBrain was first introduced to the world in October 2015 by a Bloomberg news story, though it went online in April 2015. The article in the Bloomberg news story describes RankBrain that it uses Artificial Intelligence or Al to embed great amounts of written language into mathematical entities (also known as vectors) that the computer can easily understand. If there is a word or phrase that RankBrain is not familiar with, it makes a guess what the word or phrase might mean, and find out the similar meaning and filter the results accordingly. Thus, RankBrain is quite effective in handling the never before search queries.

What is RankBrain:

RankBrain is the only live AI (artificial intelligence) that Google uses in its search result. However, Google uses machine learning instead of this live artificial intelligence for algorithm for a reason. AI is only used when search breaks, and Google’s engineers do not get any clue on how to fix it. When it comes to sorting live search results to help users by providing them the best fit for their search queries, RankBrain is used.

Is RankBrain a ranking signal?

RankBrain is called the third most crucial ranking signal of Google after and content and links. But the question is, is RankBrain really a typical ranking signal? The answer is No. At least, if you think from a traditional ranking signal perspective, it won’t fit there.

RankBrain is the way of processing search queries and finding a “best fit” for queries that are unfamiliar to Google. Every day Google processes about 15% new, unique queries that were never searched on the search engines before.

If you are thinking about why there are so many unknown queries, then it might ache your head to understand the concept. In the simplest term, there can be millions of ways of asking even a simple question. Nowadays, people are using voice search for their search queries. There are smarter devices that can take only voice. When Google does not understand your voice or the way you search a term, it uses RankBrain to bring back the best match to your query.

Earlier, RankBrain was only used for a small number of Google searches (that is about 15%). But nowadays, the uses of RankBrain has been increased, and it is now used in almost all the search queries entered into Google. Whenever Google is unsure about a query, it uses this AI to get an unbiased result for the query.

What does it mean by Know a Query Set for Google?

By rolling out Hummingbird and moving from “strings of things”, Google actually moved from inferring a match to all your search queries by using off-page and on-page factors. By seeding the algorithm with a familiar relationship, Google understands the relationships of places, people and things to each other.
To determine a query, Google at first used a database called Freebase, then WikiData became a popular option for Google. However, nowadays, it uses data fed machine learning for most queries.

How does it work?

For instance, if your content is about “red apples”, without all the optimization signals like anchor text, inbound links, and H1 tags, Google already knew that it is an edible thing that is red in color.

The database tells Google that this string is about a thing called “red apple”. Now Google pulls back all the relevant searches about red apple. This red apple might be an apple, the fruit, or a red apple computer. To help you find the most suitable one, Google shows a few alternative results in your query set. It might show you 8 results that are about apple, the fruit, and 2 results for red apple computer and vice versa.

This is the way how Google RankBrain works.

When does RankBrain influence a “query result” the most?

Irrespective of what language and from which country the search queries are, RankBrain impacts on all queries in the same way. The role of RankBrain is crucial when the query is unique and unknown to Google. Before the introduction of RankBrain Google used to show you the results that what word, it actually used in that search, instead of what you typed in.

Google RankBrain behind the scenes:

Till now, we have shared what RankBrain is and how it works in general. But this is not all. RankBrain is not mere a Natural Language Processor or NLP. With NLP, the computer can break down a long sentence and understand the intent of the users’ sentence structure and linguistics. It can understand language just like a human does, though in a different way.

Though RankBrain is close to NLP, it can infer meaning from your search query based on language alone. To pull back the best guess, RankBrain needs a database of relationships and vectors of familiar relationships between the similar search terms. If the queries are not understandable, inference occurs. However, the results are still based on that data.

How does RankBrain actually work?

Now the question is how does RankBrain actually work? Well, RankBrain uses a series of the database, based on people, places and things to determine the algorithm and its machine learning process. The queries are broken into word vectors by using a mathematical formula so that those queries can be identified. Similar words are grouped into similar addresses.

When Google experiences an unfamiliar query, it utilizes the mathematical formula to map out the relationship and find out the best fit for the query and shows several similar results depending on this.

Google is constantly refining its results based on machine learning and human interaction to enhance the match result between the user search intent and the search results that Google returns.
One important factor about RankBrain is unlike the other search engines, it does not throw away the words like “and” or “the”. It also helps in better understand the queries to deliver the best search results particularly for negative queries like using words like “without” or “not”.

As explained on The Next Web –
The role of RankBrain is to convert the textual content of search queries into word vectors, also known as distributed representation. Each of the queries has a unique coordinate address in mathematical space.

Though the process at a mathematical level is highly involved and complex, it is not overly complex at a process summary level.

The words you search, go in and get assigned a mathematical address. They are retrieved on your search query. These word interpretations are used to return search results.

The machine learning process takes the data you input to make the results more relevant next time. It might seem simple on the surface but incredibly complicated and difficult at the microlevel.

Is RankBrain optimizable?

The secret behind optimizing RankBrain is developing content by maintaining the natural flow. Don’t stuff keyword and make the content sound natural. RankBrain does not entertain content that is intentionally written by stuffing keywords. If the content is in machine language, it gets confused and pushes you back.

If you have a content site, make sure the content you write sounds natural. If you can develop content conversational, as humans do, you would be well-optimized for RankBrain, if not then you are un-optimized.

If you are a good writer, you might have thought about what more you can do to get an edge, and how you can optimize content for this ranking signal. The answer might be quite tricky. To get this answer, you have to learn why would you even want to try to get optimized for RankBrain.

Why would you try it?

RankBrain is quite beneficial for some unique cases. However, for most cases, the time and energy, you would invest to rank for a unique query, would be much better on other things. This is because you are investing your time in trying to optimize for a query that not only very few people are using, but also it is constantly changing.

The results by RankBran are specially designed to change and bring back better results. Therefore, optimizing for RankBrain is like trying to hit a moving object all the time. So, the best way is to write good content and make the content human-like and natural. You don’t need to spend time to make content optimized for this ranking signal by doing other things. So, what are you waiting for? Enhance the quality of the content and get optimized.

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