Over the course of the past several years, major players in the search engine game, including Google and Bing, have been working to improve and upgrade their algorithms and machine learning processes in order to improve the end-user’s experience. To do so, search engines have started to write logic and incorporate machine learning algorithms into their larger algorithms. That allows an algorithm to be refined according to user behavior metrics.
How are algorithms being refined in accordance with user behavior metrics? Well, search engines are now weigh user experience metrics more heavily, including time on site, bounce rate, pages per visit, return visitor rates, and conversions. Powerful algorithms are now able to use these metrics to ascertain whether or not a user is getting what he or she wants from a website, and then refine future search results accordingly. The idea is to improve user experience
“Search engines are no longer kidding around when it comes to search experience on both desktops and mobile,” explains Mitul Gandhi, the co-founder of SEOClarity. “Besides their mobile usabilility factors, Google continues to focus on improving the search experience on mobile devices with the release of AMP Pages—their tool to allow web designers to build super fast pages for mobile devices. At the same time, Apple is rumored to be building their entire Apple Search algorithm based on the actions of mobile users, based on their massive mobile phone market share.”
Furthermore, search engines are also mining data from people using their Internet browsers, such as Google Chrome, Microsoft Edge (previously Internet Explorer), and Apple Safari. These browsers are sending user behavior data back to their creators—data that can be used to further refine algorithms. The bottom line is that we will likely see the development of increasingly sophisticated search engine algorithms that will not only improve user experience, but also will also radically change the SEO game.