TL;DR:
- Google’s RankBrain is a powerful AI model that utilizes machine learning to enhance search results accuracy.
- It was introduced in 2015 to better understand search intent and move beyond keyword-based searches.
- Over time, RankBrain has become the third most important ranking signal in Google’s search engine.
- It employs machine IDs and labels to connect concepts and improve search result relevance.
- RankBrain constantly evolves, analyzing user behavior, demographics, and search context to refine its results.
- Despite its effectiveness, some users feel that Google’s search quality has declined due to factors beyond RankBrain.
- RankBrain doesn’t directly impact SEO but rewards content focused on user intent.
- The future of RankBrain depends on Google’s evolving internet strategy, as the search engine continues to adapt with AI tools like Google Bard.
Main AI News:
When you pull out your phone and type in a quick Google search to answer a question, what’s really going on? Most of us know that there’s some vast Google algorithm behind the scenes that interprets organic search and post results via a specific ranking. So far, so good. But Google also included a significant amount of AI technology in its search engine, bringing us to RankBrain. RankBrain is a machine learning model that’s deeply involved in how Google search results are returned, which means it impacts many of our online lives. Here’s an overview of how it all works.
RankBrain: The Brains Behind Google’s Search Algorithm
RankBrain is the official name for a Google AI model that uses machine learning. Machine learning means that an AI model runs through data tests and teaches itself to be more accurate. For example, an AI trained to recognize human faces can get feedback on when it’s wrong and use that feedback to make better guesses. With enough resources and time, machine learning AIs become very accurate, and few organizations have more resources or time than Google.
RankBrain is currently set up to optimize Google’s search engine algorithm, which returns results when you type something in the search bar. Google introduced AI in 2015 and 2016 to understand people’s searches and search intent accurately. It especially wanted a way to move beyond words so that the search engine could interpret the “thing” people were trying to find.
Evolution of RankBrain’s Influence
At first, RankBrain only had a minor influence on the search engine algorithm. But as it grew and received more training, it became more important. Now, Google estimates it’s the third most important ranking signal in the search engine, so it has a huge say in the results you get.
We don’t know exactly how it works because it’s a proprietary and guarded AI tech. But we do know a lot about it because of what Google openly provided to developers in the past and the other projects the company has worked on.
The Strings to Things Concept
RankBrain is part of a larger, decade-long Google endeavor to move beyond searching for words and instead search for concepts, sometimes given the moniker Strings to Things. To do this, Google uses an interpretative technology called Hummingbird. Hummingbird processes data and turns it into Machine IDs or labels to describe a Thing. That could be a person, object, color, famous monument, or anything searchable. With these advanced labels, Hummingbird links concepts together based on how they’re searched and what the text says about them.
RankBrain’s Adaptive Process
However, things constantly change, and there’s always room for error. RankBrain’s AI uses the Machine ID system to test results for accuracy and improve them. It watches how users interact with online content and uses that information to guess their intent, then guess again and again. Eventually, it creates an effective filter that prioritizes the useful, accurate search results people want (in theory, at least).
For example, if someone searches for “secrets of the Aztecs,” RankBrain helps the search engine know, based on crawled content and past searches, if it’s referring to a famous book, a theory about an Aztec legend, a video game, and so on. And if there’s a sudden burst of articles about an ancient Aztec healing diet, RankBrain shifts the concepts to create that connection. The process gets more complicated than this, but you get the idea.
The All-Encompassing Approach
To accomplish this, RankBrain looks at everything. That includes what devices make a search, the time of day a search occurs, what it knows about the demographics of a searcher, and so on. With so much data, RankBrain doesn’t need to recognize the search words. The context of the data and past results are enough to make an AI-educated guess at even the most outlandish searches.
RankBrain’s Ongoing Evolution
It’s safe to assume Google’s devs are constantly tinkering with RankBrain and that RankBrain is far from the only AI model at work in the Google search engine. After all, that search engine is a behemoth of technology, one of the most important in the world, and while we can’t see under the hood, there’s no doubt Google is always working on it or experimenting with something new. That means RankBrain is probably always getting new kinds of inputs and filters and tweaks to see what happens.
RankBrain’s Effectiveness and Controversy
RankBrain appears to be very effective at what Google wants it to do. Google released studies showing that AI is better than human developers at accurately identifying searches. But does that make the search experience better for us humans? Answers vary.
If you feel like Google’s search engine has become worse in recent years, you’re not alone. You could search for the topic right now, and RankBrain would ensure you get a long list of articles discussing how Google searches suck these days. Many believe the results lack useful information, include repetitive and unhelpful answers, or don’t understand what searchers want to see.
Is RankBrain to blame? Probably not. Theories abound that Google’s algorithm focuses too much on ad content or makes other serious mistakes that threaten search quality. Some of that may be true. But RankBrain can only train with the info it’s given. And the web is kind of a mess! There’s so much paid content, copied content, paywalls blocking high-quality content, endless SEO attempts to game the system (now including chatbot content), and other factors we don’t know about that are polluting the internet waters.
Seeking Alternative Solutions
Google seems to be struggling with this problem. RankBrain may not be making things any better (especially when it comes to niche search results). Still, it’s probably not the cause of the situation. Ad space aside, Google doesn’t want its searches to be more annoying but rather more helpful for users. The solution isn’t easy, and even Google devs don’t know the full impact RankBrain may be having. Some searchers prefer trying alternative search engines like DuckDuckGo or Bing to get results that better match their needs.
Maximizing RankBrain’s Impact
Is there a way to have RankBrain rank my content higher?
That’s the lots-of-money question! If people could design content specifically to appeal to RankBrain, maybe they could get Google to post their content higher in the search results. But RankBrain doesn’t work that way. Other pieces of the search engine algorithm handle SEO, linking, mobile optimization, and similar factors. RankBrain only looks at data to make accurate suggestions about user intent. The best way to take advantage of that is to create content that’s focused on user intent and has specific information connected to your topic instead of generic, less useful data.
The Future of RankBrain
RankBrain is designed to solve accuracy problems with search engine results and user intent. It probably won’t go away any time soon, but it’s also not a vital part of the Google search engine. What happens to RankBrain or what it becomes depends on Google’s internet strategy for the coming years. The search engine will likely change a lot in this timeframe, incorporating AI tools like Google Bard and who knows what else. We’ll have to see if RankBrain survives those changes.
Conclusion:
Google RankBrain has transformed the search engine landscape, emphasizing the importance of user intent and concept-based search. While its impact on search quality remains controversial, it underscores the need for content creators to align with user intent for better visibility in search results. The future of RankBrain holds the potential for further advancements in AI-driven search algorithms. Businesses should stay agile and adapt to evolving search engine dynamics to maintain their online presence and visibility.
