What is the Google RankBrain?
Google, with its search algorithm, uses an artificial intelligence ‘machine’ system called “RankBrain”.
How does it work, and what do we know about it?
What is RankBrain?
RankBrain is a machine-learning algorithm based on deep learning developed and used by Google to improve the relevance of search results. It can interpret new requests which have not been looked for previously.
Greg Corrado made the first official statement from Google RankBrain in October 2015. Greg said that soon after deployment, RankBrain became the third most important search ranking “factor”.
It is crucial to understand how the algorithm works and its impact on SEO.
How does RankBrain work?
The primary purpose of RankBrain is to provide the most relevant results by interpreting the meaning of whole sentences rather than focusing on the keywords. One of the facets of this algorithm is the assimilation of content.
Rankbrain efficiently manages long-tail requests and their similarities to each other (How are they connected? To which particular subjects?).
It means that Google can understand a sentence that has never been treated before by associating it with already-known sentences/concepts.
As a machine learning system, RankBrain continuously learns, paying close attention to parameters such as bounce rate or time spent on a page.
What are the implications for Google users?
- You can find information on a concept or an event without using a particular or specific word (“Which animal is at the top of the food chain?”)
- You will also get more relevant results for ambiguous searches that have several meanings (for example, “Jaguar” the car brand or “jaguar” the animal)
- If you perform a search that Google has never encountered, it will be correctly interpreted and adapted to the best-known vector.
Google doesn’t disclose the exact algorithms it uses, but we do know that its operating principles are close to the word embedding.
The word embedding approach
Choosing the right word analysis method is often essential for successful content optimization. Website owners commonly use Word frequency; however, the method has the defect of capturing little information on the context of the word(s) and their relationship to each other.
Since the late 2000s, techniques relying on artificial neural networks have become established (deep learning). This is the Word embedding.
Within a corpus, a word is not used in any way; it is contextualized in relation to the other words. Word Embedding methods build a context window for each word. We use context vectors to represent each word through a matrix. Words with similar meanings are located near the terms of the vector space.
How to optimize RankBrain?
According to Google, RankBrain cannot be optimised. It has no noticeable impact on search results, as its primary objective is to deal with queries that lack relevance.
The fact is that an SEO person can’t ignore the existence of the algorithm in your SEO actions. So, what do you do?
An SEO person can’t ignore the algorithm’s existence, though. What to do?
Expand your list of keywords beyond synonyms and co-occurrences:
- No longer create pages or content with the one keyword in mind.
- Group your targeted keywords and their variations
- Use additional lexis that has the same semantic concept
Focus on creating high value-added content
Be talkative, try to cover all aspects of the subject, and answer as many questions as you can.
Google and RankBrain intend to provide users with the most valuable and relevant results. If you share this same goal, you are more likely to succeed.
Optimize your content for your audience and not for search engines
Be natural: Although this statement may seem trivial, it is particularly true in the context of deep learning. Remember that the algorithm learns from human behaviour.
If people appreciate your content and consider it relevant, Rankbrain will naturally find it suitable.
The world of SEO is continually changing. The emergence of “deep learning” and word embedding has significant consequences.
The RankBrain system continually improves through machine learning: its goal is to provide the best content to the Internet user. All you have to do is ensure your content is as relevant and complete as possible.