Natural referencing (or SEO) is a field in perpetual evolution. With new algorithms, technical progress and changes in usage, SEO is often subject to modifications without its fundamentals being affected. Only the arrival of machine learning (or automatic learning) lets us envisage an unprecedented transformation, forcing SEO experts to adapt and review their methods.
What is machine learning? What are the changes and impacts to be expected? Your Rouen natural referencing agency explains everything to you! The first search engine in the world, Google quickly established itself as the giant of the Internet. Thus, with its algorithms, its guidelines, and its penalties, it shapes the Internet according to its desires.
And today, it is towards machine learning and deep learning that the firm seems to be moving. Already present with RankBrain, it is possible to believe it does not intend to stop there. Indeed, centered more and more on the user experience, this new method seems to respond perfectly to the new problem of Google.
Machine learning, also called “automatic learning”, is made possible thanks to the data created every day. They are the fuel of the machine. Indeed, this sub-part of artificial intelligence continuously analyzes the data that allows it to operate. More broadly, data-based learning allows computers to evolve with data. And concretely, it is a question of reproducing the human brain in a machine by submitting data to it so that it develops its knowledge.
Completely autonomous, she analyzes situations and links them to each other in practice. The ultimate goal: predictive analytics from data. That is, to make the machine capable of predicting future situations thanks to previous data. From Google’s point of view, it is no longer about defining precise rules but about learning from user experiences and making connections.
The operation of Google does not change. Only the search engine gains in speed and precision to best respond to the Internet user’s request. It is, therefore, undeniable that it is thanks to big data that it is possible to arrive at methods such as machine learning. Indeed, the data feeds the analysis. Thus, the more data the algorithm collects, the more correlations the machine can make.
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As you know, natural referencing corresponds to the work carried out to position the pages of a website favorably on specific keywords in the pages of Google search results. Only, with the arrival of machine learning, SEO is considerably upset. Indeed, the user experience has become a central point of natural referencing. Google considers the visits of Internet users to a site to study its positioning. The easier a user navigates on your site and stays there for a long time, the better positioned it will be.
For this, your site must be of high quality (good internal networking, quality content, etc.) to make the user want to continue browsing. These new criteria require a need for adaptation by web referrers. While Google was primarily a search engine, it tends to become more and more of an answer engine. Like position zero, Google makes it a point of honor to offer relevant answers to the queries of its Internet users.
What’s more, this is where AI comes in. Indeed, the more data it collects, the more the machine will create correlations and will be able to offer personalized and quality answers to Internet users. Data allows it to evolve. Thus, many changes are expected, and it is already starting.
Indeed, RankBrain, the third Google ranking criterion, uses machine learning to better interpret and respond to user queries. We can then say that it is no longer the rules that define the program but the program that defines the rules. That is to say, the arrival of machine learning will completely change those that frame traditional SEO.
Deep learning is one of the many facets of machine learning. Thus, all deep learning is necessarily machine learning, but not all machine learning is always deep learning. Its functioning is similar to that of a human brain, and the data feeds and perfects it. Before arriving at the final result, the machine will go through several stages.
For example, for an image, he receives it, analyzes it, makes a decision and is informed if it is correct or not. If it is false, the algorithm adjusts the connections so that the error does not occur again. So obviously, the machine will need to make mistakes to improve, but that will allow it to respond correctly to each request. With deep learning, it is possible to:
Like machine learning, deep learning upsets traditional SEO codes. It analyzes the existing data, decides thanks to the latter, and does not use predefined rules. The ultimate goal is effectively the maximum personalization of the search result. Only sites will continue to be created, bringing new comparative data. It is an infinite loop whose positioning criteria will gradually become extremely complex.
With the emergence of artificial intelligence and big data, machine learning and deep learning seem ready to revolutionize SEO. However, they do not evoke the end of SEO. Simply a new evolution in the face of new challenges with the objective of the user experience. It combines techniques (quality content, meta description, internal linking, etc.) and the user. According to Google, the ultimate objective is the satisfaction of Internet users. At Power Trafic, our SEO consultants are on constant watch to stay informed of new developments in their field… Their number one wish? Bring you the best support at the forefront of SEO news.
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