The past few years, a lot of theories have emerged about the forthcoming shifts in SEO strategy, so we've summed up the most talked about topics in this article. Here is how AI and machine learning will influence the future of SEO and what search marketers can do to include these new(ish) technologies in their strategy and stay on top of the game.
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Important Factors in the Ranking Algorithm
Google’s main focus is the user. From penalty systems to semantics-savvy AI, all efforts of betterment have been dedicated to improving the relevance of content for the searcher.
ago when Google introduced RankBrain, “a machine learning-based search algorithm that helps Google process search results.” And then they really lost it when it was revealed that this algorithm is “the third Digital Marketing Companies in New Orleans most important factor in the ranking algorithm along with links and content,” because this means that marketers can no longer use “old methods of gaming the rankings with false signals.” Now, only the highest-quality content will get the top ranking in Google's SERPs. RankBrain was introduced to augment Google's Hummingbird algorithm update by helping it interpret the overall context of search queries and showing users pages that do not necessarily include the words they typed, but that contain information related to the idea, domain or even location of the query. For instance, “boot” means footwear in North America, but trunk of the car in the Us.
How the algorithm works — and the best way to optimize for it — has been hotly debated for years. Google’s position is that it can’t be optimized for. In a Reddit AMA in early 2020 Google’s webmaster trends analyst Gary Illyes explained RankBrain like this:
“RankBrain is a PR-sexy, machine-learning ranking component that uses historical search data to predict what would a user most likely click on for a previously unseen query.”
gle’s most recent algorithm update, BERT, takes that idea a step further by trying to understand the intent of the searcher and focusing on concepts, rather than keywords. For example:
Google BERT
If a searcher asked whether you could pick up a prescription for someone else before BERT, the top answer would be one that didn’t answer the question; or rather, answered it in a general way. Now, it has a better understanding of the concept the user is searching for, which in this case includes the words “for someone”. How these expanding AI technologies will impact SEO is basically a Digital Marketing Companies in Las Vegas continuation of a trend that's been happening in search rankings for years — a focus on relevance, quality and value of content. As machines get better at figuring out which results to match with each search query, marketers need to get better at creating content that helps this — i.e. that users really want to read. Search engine marketers can find out for themselves what the impact of RankBrain and BERT is by paying even more attention to the SERPs and questioning every traditional SEO technique previously applied. They can collect data like common keywords or phrases that predominate titles, the sources of links on top-listed pages, and the age of the best-performing pages.