How will Google's ranking brain affect SEO in the future
Over the past decade, many custom changes have been made at the behest of Google in the search field, most of them aimed at providing relevant results. It's natural! As technology develops, changes also occur. Many technology leaders believe that in the next few years, artificial intelligence will change the way we look at technology. One of the areas that changes with machine learning is SEO. Last year, Google confirmed the existence of a machine learning artificial intelligence system called Rankbrain. This system is used to help process search results and provide relevant information to the user. SEO is forever changing, that's why we say that Google's ranking brain is going to remain permanent, which is declared as the third most important factor in the ranking algorithm after links and content. But how will this affect keywords? Well, when this artificial intelligence is used, keywords will lose their effect over time.Google is now going backwards with the various updates of Panda and Germany Email List Penguin keywords. What is important here is how many algorithms there are in Google. The main goal behind the concept of the ranking brain is to combine these important algorithms in the best possible way and provide the best search results related to the searched term to the user. For example, maybe the ranking brain prioritizes the meta title in some results, but in another search it gives more importance to the page rank. This means that the search results will never be the same. There are many factors involved here and Google has made it more difficult for SEOs to manipulate the system. In order to better understand how the ranking brain works, we must first examine Google's algorithmic changes. With a detailed analysis of these changes, a pattern appears that can show which algorithm produces the results or which one is not used.
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Once you know this, you can focus on the part of SEO that is going to be used for a specific search result. The importance of related content These days, users don't need to look for related content anymore, because related content engines offer users a list of related content under each text. Social networks like Twitter and Facebook also use the same method, that is, they suggest content that is more in line with the user's preferences. As more users go online and access information on a larger scale, this big data helps data experts formulate better machine learning algorithms and can introduce the next article or video according to the user's interests. Now, the ranking brain is gathering information, observing user behavior, and responding to users when they interact with the search results page (click on a result). Actually, this ranking brain is learning. Google wants to make little changes in rankings after algorithm updates.
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