How AI and Machine Learning Will Change Technical SEO in 2020
Artificial intelligence and machine learning are shaking up the world of technical SEO in significant ways.
Although SEO specialists aren’t in danger of losing their job, the advent of these two technologies will make updates easier and more efficient.
For the most part, SEOs have yet to write machine learning algorithms for performing technical tasks. Rather, they are using plug-ins within a content management system to perform time-consuming and tedious tasks like internal linking, tagging and reducing image size.
Many of the more tedious tasks related to improving page speed have all been improved through an impressive collection of plugins that automate these tasks.
In 2020, this trend should only continue, allowing marketers to shift some of the costs associated with technical SEO to more creative web disciplines.
Google Improves Search Experience with AI
In addition to technical SEO specialists leveraging AI tools, Google has also made significant progress with weaving this technology into its search experience. Unlike previous years, when structured data had to be marked up in order to show up in the SERPs, Google is much smarter and can reward sites with rich snippets even if the structured data markup doesn’t exist.
Here are a few areas where these improvements are already live in organic search.
We’ve seen Google reward the breadcrumb navigation in a SERP listing without breadcrumb markup actually existing on page. It is clever enough to know that it can use the directory structure of the website to build this navigation. It pieces it together in a similar manner that it pieces a meta description together if one does not exist.
Now, this doesn’t mean it will be completely accurate all the time. There will be instances where we will need to go in and specify the breadcrumb, but they must be present on-page to do so, as per Google’s recommended best practices.
Star Rating Markup
Google can automatically pick up star ratings on your site without the valid reviews or aggregate rating Schema markup.
Google rewards the thumbnail SERP feature for videos to help drive higher CTR within the video index or if exact match search queries or phrases including “video” are used.
What This Means
Brands should continue auditing SERP listing features and address reported errors of warnings, if possible, to ensure the structured data markup is as accurate as possible. Spend less time trying to mark everything up and only focus on what is critical. Use the time you’re saving to focus on creating a more engaging user experience leveraging video and/or audio when relevant.
These are only a few examples of how AI and machine learning are impacting our current task list. Google has already launched AI within its own algorithm known as RankBrain. This has been around for years and continues to learn and understand what type of content searchers might want to see based on a large collection of data points.
AI and machine learning are here to stay so it is important for SEOs to know exactly what that means and how it can impact their day-to-day. With so many tasks becoming redundant, it’s time for us to take the leap into exploring the depths of AI and machine learning, start creating our own machine learning algorithm and experiment to see how it can benefit us and our role in the marketing ecosphere.
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