Older SEO tactics and strategies are becoming less effective. While you carefully focus on keywords and backlinks. Google’s AI is rapidly evolving and dramatically changing the way search results are ranked.
All of these changes happen behind the scenes. making it increasingly difficult to understand why all your efforts aren’t working.
To make your SEO work as it should. it’s important to understand how artificial intelligence systems work so you can tailor your SEO strategy accordingly. In this blog. we’ll take a look at Google’s AI developments—RankBrain. BERT. and MUM—and how these improvements have been reshaping search for years.
Once you understand the principles of artificial intelligence. you will be better able to create content that aligns with Google’s AI-based approach. increasing your chances of ranking better in search results.
Google’s AI systems
Google has been using RankBrain AI to identify URLs since 2015. Three years later. Ben Gomes. Google’s vice president of education and former head of search. called AI the next chapter in search. At the time. Gomes explained that AI would allow Google to deliver a better user experience.
AI has created three fundamental chapters in how search works:
- From answers to travel: “To help you pick up where you left off. learn about your new hobbies and interests. we’re introducing new features in search results to help you with your frequently asked questions.”
- From queries to providing a no-questions-asked way to get to information: “We’ll help you see relevant information that’s closely related to your interests. even if you don’t have a specific query in mind.”
- From text to a more visual email list way to find information: “We’re bringing more visual content to Search results and dramatically redesigning Google Images to help you find everything you need faster and easier.”
It all started with RankBrain.
RankBrain (2015)
The RankBrain system was the very first system that helped the search engine understand how words relate to concepts.
In order for the results to be relevant to your query. the system had to understand the word as a concept. And that was Google’s first intelligent activity and its first step towards understanding content as if it were a human.
For example. if you type the search adapting to new requirements query “What is the color of the sky?”. the AI is able to understand the meaning of the word “sky” and that it has a perceived color. Google can then show the searcher a result that does not .
A few years later. Google made another big leap forward in matching words to concepts using neural matching. (Google has been using this system since 2015!)
Neuronal concordance (2018)
This system was created to help Google mobile lead understand how queries are related to pages and how they relate to concepts that are difficult to understand.
Let’s say you enter the query “Tie my shoelaces” into the search results. This combination can now have multiple variants. Thanks to neutral matching. Google is able to “understand” that the word “laces” means shoelaces and will show the queryer results about ways to tie them.