New Yandex algorithm CatBoost. What to Expect for SEO?

Recently, Yandex introduced a new machine learning algorithm based on gradient boosting, called CatBoost. This algorithm is already actively used in services such as Yandex.Weather, Yandex.Music and Yandex.Zen. It is expected that by the end of the year, CatBoost will begin to be used in search results.

What does this mean for SEO?

As always, we are most interested in how the introduction of a new algorithm will affect search traffic and website promotion processes. How much will the search algorithm change? How will he react to current sites and their content?

  • CatBoost, like any other search algorithm, is aimed at improving the quality of search. The algorithm is faster, more accurate and capable of efficiently processing a variety of data. This means that now not only text but also graphic elements placed on the page become important.
  • Manipulating search results will become even more difficult. Therefore, successful website promotion will depend on the coordinated work of the resource owner and a team of specialists.
  • With increasing demands on content quality, SEO optimization costs may increase. More quality content will be required, namely:
    • professionally written expert texts;
    • unique images;
    • video content.

What to prepare for in the coming months?

As is usually the case with changes in algorithms, search results may initially become unstable. As a result, changes in search rankings over time may be small or even unpredictable.

It is possible that there will be temporary subsidence, so-called “storms” in search results.

However, in the long term, positions should stabilize and traffic will continue to grow, perhaps at an accelerating rate. This will be the result of the fact that during the optimization process we focused on improving the quality of the resource, avoiding manipulations with search engines.

If you want to better understand how the new algorithm works, you can dive deeper into its features.

For those who prefer video materials, an interesting overview of this algorithm is available.

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