While machine learning may grab bigger headlines in relationship to self-driving cars, its role in the world of search has an impact on how web users receive information and therefore what they discover online each day. With RankBrain, Google has implemented a machine learning system that is intended to deliver better search results by applying a deeper understanding of language semantics. While it is used in a large percentage of queries, the most significant impact may be seen on search results for ambiguous and complex, multi-word queries. As one part of the overall Hummingbird algorithm, it is able to connect people with pages that are relevant but might not contain the exact search terms they used.
What is RankBrain?
Most of the searches that Google sees each day have been processed before, but 15% are new. Considering there are over 3 billion daily searches, the number of times that the search engine has to work harder to deliver the most relevant results is significant. RankBrain has the ability to identify patterns between complex, long-tail search terms and use these as clues to the meaning of queries it has not seen previously. When someone submits a seemingly disconnected set of terms to initiate a search, it can determine the concepts that might be connected and guess at the best results. RankBrain is not pre-programmed to deliver results in a certain way. It has been fed historical data and will learn about the search process over time so that it can yield an educated guess when the answer is unknown.
A few years ago, Google showed us the connection between “things, not strings” with the Knowledge Graph. Rather than matching keywords and queries, it uses a more sophisticated way of linking information, yielding relevant information on known topics, or things. Search the name Marie Curie, and you will find her occupation, biographical details, discoveries, quotes, and a row of other related people including her family members and other scientists. Google easily can deliver information on Marie Curie and present it as a snapshot of connected facts because it interprets the query as more than a string of letters that make up her name.
Why Does RankBrain Matter?
With the introduction of Hummingbird, Google applied its ability to understand the meaning of terms and queries on a broader scale. The new algorithm was a major shift toward ranking and search that is focused on contextual meaning rather than keywords alone. Websites that focused on providing more complex responses to user needs became the focus, and keyword stuffing and density became outmoded techniques. Keywords themselves certainly didn’t become obsolete, but synonyms and related terms became more valuable as Google understood he associations between words and the intent behind using them in a query.
When considering the impact of Google’s new machine learning system on SEO efforts already in place, there is no need to panic. If you already are focused on delivering information that serves customer needs, Google should be able to connect them with your content more easily, even if their queries are worded ambiguously. Continue to incorporate keywords in natural, strategic ways in titles, headers, sub-headers, and paragraphs. High-quality, readable content with natural usage of keywords certainly benefits your customers, and it is aligned with the increasing ability of search engines to understand the intent behind queries.
Final Thoughts on RankBrain
RankBrain is another advance in semantic search, but it is aligned with SEO best practices your digital marketing campaigns already should be following. Since this is a machine learning system that will evolve over time, put it on your radar, and for now use it as confirmation that your focus on content creation is right on target. If you would like more information on RankBrain, contact one of our experts at Premiere Creative . Call (973) 346-8100!