Source:- it.toolbox.com
Tools that facilitate (and accelerate) work on-site optimization and make the content better, more precisely and better marked are of increasing importance. Such tools and services are mostly based on artificial intelligence, and on this occasion, we investigate how SEO can affect SEO optimization.
Since Google is still the most popular search engine in the world, SEO experts are mostly guided by the latest solutions and changes coming from that company.
Artificial Intelligence (AI), which this technological giant uses, probably exceeds our most optimistic ideas. Although Google has never fully discovered how the algorithm works, something is still known to us. We know, for example, that the so-called Google RankBrain uses machine learning in order to present users with the most relevant and high-quality search results.
We also know that Google has announced a far greater significance of visual content in searches, especially images and videos, as well as moving from simple responses to tracking the so-called. Search path, i.e. the time when users pass, for example, from the initial interest for a particular product to its ordering or online purchase.
We present some important ways to use AI to improve SEO optimization.
Well, let’s start.
Code validation
Considering that the unauthorized code on the site is considered one of the SEO errors that occur during the creation of the site, it is clear that the validation of the source code should be taken into account. Some of the tools for controlling and correcting HTML code are based on algorithms today that border with AI when it comes to analyzing HTML tags.
These tools indicate whether the site is valid or that it complies with World Wide Wed Consortium (W3C) standards and warns of errors. As a result, of course, it generates a much cleaner and more quality code.
Why Is It Important For SEO?
If you want Google and other search engines to successfully index content on your site, it’s important that you validate the code for each page of the site. Otherwise, you can lose credibility with Google due to poor coding practices, which can easily lead to a drop in position when ranking in search.
Domain authority 2.0
Different parameters are used daily in site optimization. Several companies who are considered leaders in the SEO industry, including the leading Moz, Ahrefs, and Majestic, have been developing and continually improving their algorithms for calculating domain authority, the authority of individual pages, indicators of the likelihood of ranking domain searches and many others for decades.
Domain Authority (DA) is one of the most well-known and most popular metrics that point to the assessment of the quality of one domain and the likelihood that the site will be better ranked in search compared to others, primarily on the competition. Developed by Moz company, it is calculated algorithmically and is expressed in values from 0 to 100, where the higher digit shows a higher quality domain.
Recently, the algorithm has been improved and now, in its application, artificial intelligence and machine learning are becoming more apparent.
Domain Authority 2.0, as it was officially called up by Moz, is tasked with counting domains manipulated in sales bids, as well as those who are evidently dealing with the sale and purchase of backlinks or applying some of the black hat SEO techniques.
Many people (wrongly) think that domain authority is one of the factors affecting search results on Google. It’s not. But, as Moz explained recently, YES in a large percentage accurately predicts the potential of a site for ranking. An improved version now makes it even more precise.
How Does It Affect SEO?
The new DA is based on a smart neural mechanism that recognizes when a site manipulates links in some way or uses undesirable SEO techniques and therefore punishes it with lower authority.
Due to the launch of the new DA in February 2019, almost all sites had a fall in authority. Regular sites, as they pointed out in Moz, experienced a 6% drop on average, while those who manipulate links, resell domains at auctions, and deal with unsuccessful actions facing the decline of DA, reaching as much as 98%.
Artificial intelligence, in this case, contributes to a much fairer Internet, but also to more quality search results that are presented to users.
Improved image search results
Considering that Google has announced a greater significance of visual content in search, and a new way to rank photos and videos in search, this browser now uses the AI for the intelligent design of the AMP story, as part of an open source library that anyone can use to create own content.
As explains Cathy Edwards, the director of the engineering department at Google, that’s exactly what will be better positioned in the search. At the end of 2018, it announced several new features that will help users easily find visual information and successfully perform a search where it’s important to have a visual reference.
In addition, sites that contain a large number of photos and other visual content, most often use AI tools that perform automatic content recognition and tagging.
How does artificial intelligence know that the picture is, say, wood? By analyzing shapes and edges, it compares contours with already existing tree images in its base, then it comes to a calculation in which percentage of the contour and color of the particular picture coincide with what is in the base.
What does this mean in practice?
If it turns out that there is, for example, 60% of the probability of the tree, then it is estimated whether it is the right tree or not, according to the parameters set in a particular place.
In other words, if you are asked to confirm what was discovered with security greater than 80%, in this particular case, the tree would not be designated as one of the elements in the picture (because the probability is 60%).
Why Is It Important For SEO?
Optimizing images and video content has always been very important for SEO optimization. Today, however, the use of AI in image marking tools makes it easier for professionals to work so that they may not soon need a human hand for such an action.
This speeds up the job, but it should still be taken into account and subsequently controlled by each AI result since it can be defective. Paradoxically, these are usually mistaken that people would not otherwise make.
Neural synchronism matching
When it comes to synonyms, the most significant is the latent semantic indexing method (latent semantic indexing, LSI). This is a method designed to improve the accuracy, accuracy, and relevance of the information returned by the search engine after the query.
However, Google began using neural matching to better understand synonyms. This AI method helps to connect concepts with words. As Danny Sullivan, a search engine at Google officially explained, a neural matching affects 30% of search queries.
This technique was also mentioned at events on the occasion of the 20th anniversary of Google when it was pointed out that artificial neural networks help turn words into a representation of basic concepts and then compare them with concepts in query and concepts in results.
What does SEO mean?
This means that keywords do not have the same importance in optimization in themselves. Much more attention should be paid to the entire context of the content, the concept on which the content is based and the use of as many sanitizers as possible to help search engines determine the relevance for a specific query.