The top four SEO trends that are expected to dominate in 2023

Here are the top four SEO trends that are expected to dominate in 2023:


Google began rolling out the Page Experience Algorithm gradually in 2021. This algorithm update will affect a variety of user experience signals, including the Core Web Vitals, which is essentially an assessment of a user’s overall experience with the web page.

The update began with mobile and is expected to be completed by the end of March 2022 — the final rollout will include desktop search results. As a result, we can predict that page experience will be a more important ranking factor for both mobile and desktop websites.

The page experience is more than just mobile friendliness and responsiveness. The Page Experience Algorithm evaluates metrics such as loading speed, interactivity, visual stability, and HTTPS security.


After years of anticipation, Google finally completed the rollout of Mobile-First Indexing (MFI) in March 2021. This means that Google will take priority indexing and placings of mobile-friendly websites.
By this point, all web pages had been converted to MFI. We can forecast that non-mobile-responsive websites and sites with poor UX will suffer greatly in search rankings in 2022 if this update is combined with the Page Experience Algorithm.


Aside from the major updates that Google has recently put in place, they have also made minor changes such as the Passage Ranking Update. This update is closely related to Google BERT, a deep learning algorithm that aids search engines in processing words in relation to the context of other words.

With the execution of the Passage Ranking Upgrade, Google can now index not only entire web pages, but also independent passages from those pages, also known as featured snippets.

This is incredibly beneficial for very particular search queries and voice search results, making it easier for users to find out the exact answer they seek. And, as users become more deliberate and specific in how they sequence their search queries, featured snippets are expected to play a larger role in the coming years.


Google also released an update to their Multitask Unified Model (MUM) in May 2021, which is a natural language model similar to but significantly better than BERT.

MUM assists Google in presenting more thorough solutions for complex search queries by utilizing contextual information. This differs from the Passage Ranking Update in that MUM is multimodal, which means it can understand information from other sources (pictures, webpages, etc.) at the same time and give you lots more relevant content in response. It also aims to break down language and format barriers in order to provide better search results.

The following is an example from Google: You can photograph your boots and ask, “Can I use this to hike Mt. Fuji?” Google can analyze the image and the text query using MUM and the power of AI, and then point you to a blog with a list of recommended hiking gear.

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