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Google's RankBrain brings machine learning to search results

Google’s RankBrain brings machine learning to search results

Last week Google revealed it has been using RankBrain, a machine learning process, to help return results for a large number of search queries. Google began a slow, quiet rollout of the update in early 2015, and RankBrain has been completely live and in use for searches globally for the past several months.

With the addition of RankBrain to its algorithm, Google is attempting to better predict what information people are searching for by using past queries to learn user intent. This will help Google return higher-quality results for new complex queries. In an interview with Bloomberg, senior research scientist, Greg Corrado said RankBrain is now processing a “very large fraction” of search queries.

From strings to things

In the early days of search, Google was looking for specific strings — or combinations of letters — on web pages. For example, a search for “estate planning” would return only pages containing that specific string of letters. This reliance on strings made keyword stuffing a popular SEO tactic. The more often you could fit your keywords onto a page the better.

Google, of course, matured and got more proficient at recognizing similar words through a method called stemming. With stemming, a search for “lawyer” would also return pages containing the word “lawyers,” since Google could recognize those to be variations of the same term. It also began to learn synonyms, so that a search for “lawyer” might return pages containing the words “attorney” or “attorneys.”

Moving toward intelligent search

With the release of Hummingbird, Google began to move away from looking for specific letter combinations and toward looking for things, or entities. An entity is a person, place or object — a concrete data point. This allowed Google to start looking for relationships between search queries and other entities. Post-Hummingbird, a search for “estate planning” might return pages containing terms Google has decided are related to estate planning, like “trusts” or “advance directive.”

Google is very good at establishing relationships with known entities. For example, when you search for “Ginsburg,” Google assumes you mean Supreme Court Justice, Ruth Bader Ginsburg. It also suggests that you may be misspelling the last name of poet, Allen Ginsberg.

With Knowledge Graph, Google can draw connections between data points. Because of this you can find information on an entity even if you don’t know they exact term you are looking for. For example, Google can also return results for Ruth Bader Ginsburg when you search for “Jane Ginsburg mother.”

Meeting the unknown

Every day, however, hundreds of millions of searches are performed for terms Google has never before encountered. In these instances, Google is less proficient at making correlations that the human mind would naturally make. It tends to throw out a kitchen sink of results — pages it is guessing could be related to the original search query. Some are relevant. Some may not be.

How can results for these complex, unknown queries become more accurate?

Enter RankBrain

As smart as Google’s algorithm has become, its intelligence still largely depends on an actual human somewhere entering some sort of data. RankBrain is Google’s attempt to add a much greater degree of automation to the process.

Search Engine Land estimates Google handles more than 450 million queries a day that contain a combination of words it has never seen. Many of these are likely multi-word, long-tail searches. RankBrain is intended to help handle these unknowns by learning to recognize patterns and connections and use them interpret new search queries more effectively.

As the algorithm becomes smarter, it will be able to better understand the millions of new complex queries it sees every day and determine how (and whether) those searches are associated with known topics. This will help it better predict user intent and understand which pages will be most helpful to the searcher.

RankBrain does not replace Hummingbird. Rather, it is a part of the overall Hummingbird algorithm. According to Google, RankBrain has quickly become a major piece of that algorithm. In his interview with Bloomberg, 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.”

A ranking signal is any factor Google uses to determine how to rank web pages in results. Ranking signals are usually associated with page content. Words, titles and mobile-friendliness, for example, are all ranking signals.

Now, Google is referring to a piece of its algorithm as a ranking signal. It is still unclear exactly what this means. Will RankBrain produce a score, similar to Google’s mobile and user-friendliness scores, that will contribute to a page’s ranking? Is it assessing quality by analyzing related terms? Google may answer these questions in time, but for now it is remaining silent about the details.

Does this change search marketing?

If you are already using white hat search marketing techniques that fall within Google’s guidelines, not a lot will change. Google’s algorithm is attempting to learn to think more like an actual human being so that it can provide better results and a better user experience.

Google’s foray into machine learning likely indicates that Google is anticipating further growth in voice search and mobile search. Voice queries are by their nature usually more complex. It also confirms Google’s interest in micromoments – or specific periods of time (and place) for which searchers want a particular set of results for a given query.

None of this is new or revolutionary, and Google has been moving in this direction for many years. You still need to focus on providing helpful, high-quality content, easy to navigate pages and a mobile-friendly experience focused on the visitor. You also need to continue to accumulate social proof, especially in the form of reviews. As Google’s machines continue to learn, the algorithm should reward those who have been doing SEO the right way all along.


Kristen Friend
Kristen Friend is a 1999 graduate of Indiana University, with Bachelors Degrees in both journalism and religious studies. In 2003, she graduated from the International Academy of Design. She is a contributor to the Bigger Law Firm magazine, and is the Art Director for Adviatech (Custom Legal Marketing's parent company). When she isn't making law firms look their best, Kristen can be found hiking up Mt. Tamalpais or inventing gluten free baking recipes.
  • Nikolay Stoyanov

    Excellent article Kristen! As you said, Google is trying to adapt to mobile devices and voice search. If something else becomes important, do you think that they will modify RankBrain? (even if it hasn’t reached its full potential)

  • Kristen

    Thank you! My short answer is both yes and no. I’ll explain.

    Yes, I think Google will continue to modify its algorithm, both through changes to RankBrain and through some as of yet unnamed piece of the puzzle, indefinitely – or at least until the internet as we know it no longer exists.

    Google almost never leaves a major piece of its algorithm alone; it is constantly updating. Something will at some point force Google to create a new, big, named part for its algorithm, but I don’t see that rendering RankBrain obsolete. The fact that RankBrain rose so quickly to become an integral ranking signal is a sign of its importance, and I think it will continue to evolve.

    With RankBrain, Google is primarily interested in learning how people think and how we make associations, so that its algorithm can learn to think in the same way. I do not believe that this fundamental interest in predicting human behavior and understanding human intent will change, even with the adoption of some as of yet undiscovered technology. The need to be able to predict what we want is too integral to Google’s business model.

    So, no, I don’t anticipate Google changing the underlying objective of RankBrain, though the programming itself will need to be modified.

    Also, I think Google is doing more than trying to adapt to mobile devices; I think it is trying to force website owners to recognize the reality of mobile usage. Google is actively pushing for mobile-friendly design, its punishing sites that aren’t mobile-friendly, and it is incredibly interested in micro-moments – the right here, right now searches that are most prevalent on smartphones. Google announced the Google assistant in May, which it describes as a “two-way dialogue between you and Google that understands your world.” It wants people to use the assistant to organize their entire lives. It’s not just about search, it’s about scheduling and saving money and finding colleagues and exploring your environment through any device you have.

    I can’t pretend to know what Google is working on now behind closed doors, but I do think that whatever it is, it will involve using data to know as much about you and me and every other user – and how we all think – in order to proactively serve us information, anytime.

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