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Google RankBrain Vs. Google Neural Matching: Just The Facts

April 11, 2019 Kathy Bryan

artificial intelligence google rankbrain

Last month, in a series of tweets, Google clarified how neural matching, first announced last September, differs from RankBrain and what marketers can do to help their web pages rank in Google’s search engine results pages.

What Is Google RankBrain?

Using artificial intelligence, RankBrain allows Google to interpret the concepts contained within web pages. Through this process, Google is able to match web pages to user queries based on concepts instead of just keywords. RankBrain was introduced by Google in 2016.

What Is Google Neural Matching?

Also deploying artificial intelligence, neural matching helps Google align synonyms with searched keywords to better understand the true intention of queries. Neural matching was introduced by Google in 2018.

How Do Google RankBrain And Google Neural Matching Work Together?

Google RankBrain interprets the concept within web content while Google neural matching deciphers the intention of user queries. Once web concepts and search intentions are identified, Google is able to match the most relevant concepts to the interpreted purpose of each Google query.

Why Are Google RankBrain And Google Neural Matching Needed?

According to Google, 15% of all queries are brand new, meaning they contain a unique set of keywords that has yet to be searched by any other Google user. The Google search algorithm, inclusive of RankBrain and neural matching, allows Google to provide relevant results for these brand new queries.

How Is Google Advancing Search To Benefit User Journeys?

Google Advancing Search To Benefit User Journeys

For the past two decades, according to Ben Gomes, Senior Vice President of Search, News and Assistant at Google, the core principles of Google search have not wavered. Google keeps their “focus on the user” as they work to provide the “most relevant, highest quality information as quickly as possible.”

But consistency of purpose does not imply stagnation of practice. Google is continuously optimizing their search results. In fact, in 2017, Google performed 200,000 search-related experiments that drove more than 2,400 search-related changes.

Recently, Google is focused on better aligning search results with natural user journeys to help users progress with their learning, exploration and decision making. According to Nick Fox, Vice President of Product and Design for Google Search and Assistant, Google added a Topic Layer to their Knowledge Graph to better address search journeys. While the Google Knowledge Graph, introduced in 2012, catalogs connections between people, places, things and facts so Google can provide results relevant to keywords searched, the Topic Layer of the Google Knowledge Graph analyzes subtopic patterns to add the dimension of time to the Knowledge Graph and show how familiarity can enhance understanding.

What Can Marketers Do To Improve Their Google Search Rankings?

Quality content continues to become increasingly important as Google search rankings are based less on keyword inclusion and more on providing value to Google users. With Google RankBrain and neural matching working together to match the content that best matches search intentions, marketers focused on enhancing their SEO results are encouraged to develop content that addresses the needs of their target audiences throughout the user journey.

Reimagining Your Search Marketing?

Contact Digital Media Solutions today.

About the Author

Kathy Bryan

Kathy Bryan is the Senior Vice President of Corporate Marketing and Communications at Digital Media Solutions (DMS), the fastest-growing independent digital performance marketing company. In this role, Kathy is responsible for all aspects of marketing and communications for DMS and its subsidiary brands. Since its inception, DMS has evolved into an award-winning, full-service performance marketing company demonstrating incredible year-over-year growth which has earned recognition on the Inc. 5000 list in 2014, 2015, 2016, 2017 and 2018.

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