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Machine Learning and Analysis of Site Position Data

What are Google's machine learning algorithms, and how do they help to get higher positions in SERP

Photo by KOBU Agency on Unsplash
Photo by KOBU Agency on Unsplash

Machine learning (ML) has been actively developing over the past decade. And we must admit that progress has achieved impressive success. However, despite the active development of ML, many SEO specialists do not use this option yet, since the use of neural networks is still costly.

Meanwhile, Google is increasingly introducing algorithms to rank sites in SERP. Therefore, if the programmer promotes a personal website or working on client sites, one definitely needs to know how Google’s next-generation algorithms work and take them into account. So, what do search engines teach neural networks, and how can this affect a site’s ranking?

How does machine learning affect search engine rankings?

For the site to be ranked higher, the website owner needs to publish fresh content regularly. However, there are two key requirements:

  • The content must be relevant;
  • It should also be useful to users.

The progress of bots has already reached such an extent that they can independently decide whether this piece of copy can be useful to the user. Google assessors can understand texts and determine the quality of information. Therefore, it is no longer enough to write something and just fill the text with keywords. The information contained in the article should be useful, and the topic should be fully disclosed.

The main principle of SEO is to optimize a site not only for the requirements of search robots but also to provide important information to users. Google also measures the user experience and can determine whether the content on the site motivates users to interact with the company or not.

ML-based algorithms constantly receive new data for analysis and learn to decipher queries superficially and understand them. Thanks to this, Google provides users with better and more interesting content, which keeps users’ interest in the search engine itself. Therefore, Google Machine Learning will continue to evolve, and the requirements for content will be increasingly high.

If the content on a site allows users to get a positive experience, then it will be easier for such a site to reach the top 10 of the SERP. Artificial intelligence is becoming more and more effective, and every day it learns to analyze texts deeper and deeper.

Google algorithms based on neural networks

One of the main tools for analyzing sites is a neural network. The principle operation of a neural network is similar to the principle of the operation of neurons in the human brain. Thanks to certain algorithms, the neural network analyzes the content and gives it its own assessment. Such technologies significantly improve the quality of search engine robots and content analysis.

The exact algorithm of the Google neural network is not disclosed and is a corporate secret. Nevertheless, the company’s employees regularly announce updates on their blogs and provide users with tips for optimizing sites. Google’s system of algorithms is collectively called Core Algorithms. This system includes dozens of additional algorithms. Here’s a brief overview of some of them.

  1. Panda. This algorithm is one of the oldest among the currently operating, and it was launched back in 2011. The Panda algorithm was created to identify low-quality content, duplicates, and non-original text.
  2. Penguin is a newer algorithm designed specifically to deal with low-quality links. If a company posts backlinks to its website on dingy platforms or link exchanges, there is a risk of being penalized by the Penguin algorithm. To not encounter such problems, it is recommended to monitor the links leading to the website regularly. If there are so-called "junk" links, it is best to remove them as soon as possible. Use the Disavow Tool for this.
  3. Hummingbird. This algorithm was launched by Google back in 2013 and had an important function of determining the quality and meaning of content. Before the development of Hummingbird, search robots could only identify the semantic parts of texts, and optimization was sufficient only for keywords. Hummingbird analyzes the whole text and offers users pages, even if there is no verbatim query that the user entered into the search bar. If the content can be helpful to the reader, Hummingbird will suggest it.
  4. RankBrain. It is a unique Google system that combines artificial intelligence and machine learning. RankBrain has been operating since 2015 and is designed to compare texts on a specific site with the content on other sites in the SERP. Based on comparison results, Google decides what information should be shown to the user. RankBrain also takes into account the behavior of other users, which also helps to determine the usefulness and relevance of the content.
  5. Opossum. This algorithm was launched in 2016 and was developed to distinguish between general and regional queries. The main task of this algorithm is to remove companies with the same address, phone number, and other contacts from the search results. At the same time, it increases the ranking of companies with local addresses and contacts.

New BERT and SMITH algorithms based on machine learning

The new BERT algorithm is designed specifically for content analysis based on neural networks. It is used to increase the relevance of the results by processing not keywords but the meaning and quality of the content.

The current algorithm performs analysis directly on keywords or phrases, which allows them to select relevant results. BERT is a fundamentally different idea. The task of Google specialists is to teach the algorithm to assess the query, not literally, but to determine its essence. For this, an analysis will be used not only for keywords but also for other words, including definitions and prepositions. Thus, BERT aims to exclude content that does not correspond to the essence of the query from the search results.

The algorithm was announced in October 2019, but so far, it has not been launched in the final version. Google continues to develop the algorithm. The algorithm is tested on long search queries that cannot be divided into blocks to lose the phrase’s meaning. BERT is not used when processing short queries, including those with brand names. In the future, Google plans to use this algorithm for most of the world’s languages. To date, Google has not officially announced an exact launch date.

In addition, Google has already announced another algorithm, SMITH. It is superior to BERT in understanding long queries and documents. The SMITH algorithm tries to understand entire documents, while BERT processes individual fragments. However, Google developers have not announced the start of its use so far.

How to use knowledge of ML algorithms for SEO?

So, what should an SEO expert do with this information? There are a few simple steps to take to improve the site’s rankings.

  • Improving meta tags. It is recommended to rewrite them from time to time so that all meta tags are logically correct. Information in meta tags should reflect the kernel of the content.
  • Creating content around the keyword. One way or another, the algorithms still analyze keywords, so it is important to choose the right keywords and build content around the semantic core. Use modern keyword collecting tools like SE Ranking and Similarweb.
  • Write informative and useful content. The more information the user receives from the article, the higher the chances that search robots will boost the page in the search results.
  • Think of readability. Try to write in clear language. Structure texts. Highlight key points. Do not forget about linking to articles that can provide additional information on the topic.
  • Ask experts. If the knowledge in any area is weak, provide quotes from specialists. Expert content has become especially highly ranked by search engines in the medical niche – for this; even an additional E-A-T algorithm was introduced.

Summary

Google’s search algorithms are a complex system that is constantly evolving. The use of algorithms is intended to leave only high-quality content in the search results that fully meet users’ expectations. We can expect that there will be even more algorithms based on neural networks soon. Therefore, if the programmer does SEO for a personal site, it is better to rebuild the strategy to get ahead of the competition.


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