In SEO , machine learning is often seen as a further development of the already complex search algorithm. With the help of automated processes, the user should be shown the best search result. But that’s just one aspect that webmasters will have to consider in the future. There is also the danger that the competition will pull away with self-learning programs.

Experts from the online marketing agency artaxo regularly explain relevant topics from the field of search engine optimization (SEO).

What is machine learning and how does it work?

Machine learning is a subset of artificial intelligence (AI) . This aims to enable computers with collected data to make decisions that are comparable to those of humans . The machine learning sub-discipline is specifically about computers using automated algorithms to recognize precise patterns in data, improve the results and make predictions through learning processes and experience. The machines learn by themselves . This automatic learning process can even go so far that people can hardly understand itis. This happened, for example, in Facebook’s AI labs. There, two chatbots suddenly communicated in their own language that people no longer understood, after which the Facebook AI experiment was stopped .

Algorithms work with the technology of neural networks , with which the machine can recognize recurring patterns in information and structure the information based on similarities – comparable to the human brain . On the basis of complex mathematical models, new insights can be made for future events and processes can be improved. This process consists of different successive levels and is repeated one by one, making the result of the algorithm more and more accurate . This behavior is also similar to a person who tries again and again until he has found the right way for himself in the end.

Machine Learning and SEO: Current Developments

Machine learning is not a new phenomenon in search engine optimization. For example, it is already used today in speech recognition , image search, Google Translate and of course RankBrain . However, it is not entirely clear where and to what extent Google uses machine learning.

But if you have the Google Translator installed as an app, you already know how good Google is at interpreting images . Text information is recognized and translated live. It wouldn’t have gotten this far without machine learning.

With Google Lens you are already one step further. Here not only texts, but any data are interpreted and enriched with information: sights, animals and maybe even soon people. Although it hasn’t been confirmed yet, this could soon be a new ranking factor: the content of images. Then text-free image blogs could also achieve adequate rankings and shop-typical SEO texts would disappear. The significance of this for the YouTube ranking is still unclear.

Speech recognition is also based on machine learning , is currently becoming more and more popular with Google Home and Co, and is making great strides in its development. Just this year , Google CEO Sundar Pichai revealed at Google I/O 2017 that the error rate in speech recognition is now only 4.9 percent. If Google employees had to speak every single word in every language and dialect to train the assistant, this development would never have happened. The increasing popularity of voice control is consequently changing the orientation of continuous text. Whole word phrases like FAQs are becoming more and more interesting.

RankBrain is part of the Google algorithm, which has been using machine learning to translate and answer content-related search queries into a simple query since 2015. You can read about the importance of RankBrain for SEO in our last post in our series .

How is machine learning changing Google search?

Using machine learning, Google’s search algorithm learns to understand things even better. As a result, the search engine is increasingly able to offer users even more suitable results for individual search queries. It is therefore becoming essential for website operators to offer users exactly what they are looking for in order to land at the top of the search results. Some experts are therefore reluctant to speak of Search Engine Optimization and rather of Search Experience Optimization .

Another important point is personalization . For example, if you have searched for “hairdresser”, the Google results are already related to your location and are therefore displayed in a personalized way. This is (probably) just the beginning. Of course, Google’s striving to deliver the best result at all times cannot be guaranteed for generalized results.

One likes short articles, the other prefers long articles. Commentary versus technical report, deserts of text versus richness in images, and so on. The one best document could soon no longer exist – and then suddenly completely new possibilities open up again. Because for each keyword there could be individual niches in the future. It would then look like this: small sites that hardly have a chance against the big players try to do everything differently than their big competitors in order to compete for traffic with the same content but different presentation. Being different from the competition could then pay off more than ever before.

And how is machine learning changing the work of webmasters?

On the other hand, machine learning is not only changing Google’s sacred search algorithms, but also the way webmasters can design their websites and create and adapt content in the future. Moz SEO experts have long used machine learning to predict how well a document will rank. Yelp uses self-learning programs to categorize the images uploaded by users . And you’ve probably all stumbled across Amazon’s automated product suggestions.

While it seems that only large companies rely on self-learning machines, the concept of machine learning is also hidden behind the continuous text of countless websites : Automated writing programs are increasingly creating the textual information that is so important for search engines. Thanks to automated training, the artificial writers are getting better and more efficient. Fully automated content creation is already possible . Every webmaster should follow closely how this is going to continue. The infinite scalability proves the enormous potential of this technology.

Machine learning in the future and its impact on ranking

Machine learning is definitely a topic that Google will focus on in the future, as machines can implement many things better and faster than humans. According to Google’s Eric Schmidt , ” something really big  is just beginning ” with machine learning . As already described in our last article on RankBrain , the further development of Google’s search algorithm is currently being initiated by a Google developer. In the future, however, algorithms will probably take care of this development to a large extent.

This is a very important point. Because while humans can only consider factors that strike them, a self-learning algorithm takes everything into account . An example: It becomes clear that scientific articles in which certain words are omitted are particularly well received by readers. These words could henceforth be a negative signal for Google. Taking individual factors into account could then become almost impossible. It’s all about understanding people .

According to Google’s  Gary Illyes , Google uses machine learning to produce new signals and signal aggregations and see if they improve page rankings and quality. However, he does not expect that the entire ranking system or the main algorithm of Google will be based on machine learning in the near future . This is because debugging machine learning decisions is almost impossible. After all, you don’t want to make the same “mistake” as Facebook , so that in the end no one understands the algorithm except the algorithm itself.


Above all, machine learning means that Google is getting smarter. Google could understand our needs better than we do and thus provide the best results. So you need to understand your users even better in the future than you have in the past. On the other hand, new possibilities are also opening up: self-learning text creation programs, intelligent data evaluation, personalized search results. In some industries, machine learning could be a real game changer that is worth keeping an eye on. However, one should not expect a change that is too rapid – the fear of losing control is still too great.

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