AI/Machine learning is not entirely new, but as the technology behind it continues to evolve, it’s important to think about its dynamic impact on technical SEO, content, link building, and links.
The latest Google updates are aiming to give SEOs more freedom to focus on the user rather than on bots. Specifically, algorithms that understand natural language will be utilised even more in the coming years—and that can change how Google determines the types of content that will rank well. These algorithms will no doubt have a huge impact on how SEOs should approach optimisation and content building.
What Does Machine Learning Mean For Search Engine Rankings?
Passage-based indexing will be implemented by Google. This technology allows it to recognise individual passages on a particular page to be processed as possibly highly relevant for a certain query, even if those passages don’t reflect the main theme of the page. This change is expected to affect around 7% of search queries across every language.
Another important change to note about passage-based indexing is that Bidirectional Encoder Representations from Transformers (BERT) will be applied to almost 100% of all queries. BERT is the neural network-based method that Bing and Google use for natural language pre-training to enhance the way they recognise the context of words. It is set to be applied to almost every query made in English on Google search. Prior to that, it was applied to one in 10 queries. Widening BERT’s application should enhance the way Google understands search intent and content.
Better For Misspelled Queries
According to Google, one in 10 search queries are misspelled, so they are also advancing language understanding to enhance model edge cases where spelling errors are involved—like when context is needed to determine a misspelling or in cases where there are severely misspelled words. If you are still trying to optimise your site for misspellings, it may be time to switch your focus on other important things, as Google was expected to roll out this change towards the end of October 2020.
What It All Means For SEOs And The Future Of Search Engines
Machine learning and natural language processing can dramatically improve user experience. For one thing, the technology that powers passage indexation lets Google identify pages with an individual section that match a query, even if the rest of that page is just slightly relevant. There is more focus on the audience instead of search crawlers—which may ultimately be beneficial from the perspective of ranking and content.
When Google introduced Featured Snippets and shifted its focus on topical authority, focused content became the standard. Search engines preferred topical authority and content—and this has restricted many SEOs into a mindset that search bots and users should be prioritised equally when writing content.
This kind of thinking is quickly becoming outdated because of machine learning. It’s time to shift to creating content that suits a searcher’s intent, in a form that makes sense for the user and the subject matter.
That said, it’s still important to make your site googlebot-friendly for the sake of technical SEO. Many experts also DON’T recommend abandoning keyword research altogether, but instead adapting it to intent research. After all, various keywords can be used to express the same intent—and you still need to find out what those are. Besides, Google expects passage indexation to affect only 7% of search queries, so keyword research should remain a vital part of SEO for the foreseeable future.
The Bottom Line
As always, Google’s goal is to provide its users with the information that they want. And if you want your website to rank well then, it’s incumbent upon you to do the same. Omni can help… talk to us if you need comprehensive, future-proof SEO services.