ⓘ Yandex Zen

                                     

ⓘ Yandex Zen

Yandex Zen is a personal recommendations service created by Yandex that uses machine learning technology.

Zen creates a feed of content that automatically adjusts to the interests of a user. The selection of content is based on the analysis of browsing history, user-specified preferences, location, time of day and other factors.

Zen has a weekly active user audience of more than 20 million.

                                     

1. Technology

Zen is an example of the implementation of a specialized artificial intelligence technology.

To analyze the interests and preferences of users, Yandex uses information about sites that have been visited, as well as user-specified interests.

The system analyzes the users favorite sites and other behaviors with the aim of creating a unique model of the users preferences. With an increasing amount of data about the user, the system can offer the user more relevant and topical content, including content from sources unfamiliar to the user. Zen adapts to the changing interests of the user. For example, if a user begins to read about architecture, content on this subject will appear in their content feed more often.

The service is available as part of the desktop and mobile versions of Yandex Browser and in Yandex Launcher.

Zen, Launcher and Browser belong to the" Discovery” technology category services and apps that use artificial intelligence to adapt to a user.

The technology that underlies Zen was adapted by Yandex and CERN for use in the Large Hadron Collider. It is used to provide in-depth analysis of the results of physics experiments taking place at the LHС.

                                     

2. Media platform

In 2017, Yandex announced the launch of a platform that allows companies and independent authors to publish media content directly to Zen. The platform also allows popular authors to earn money by using micropayment channels and ads. According to Zen Media Director Daniel Trabun, the company plans to pay up to $1 million to the best authors of publications in 2017.

Prior to the launch of the platform, Zen feeds consisted only of publications selected from publicly available sources.

                                     

3. History

In 1997, Yandex began research into natural language processing, machine learning and recommendation systems. In 2009, the proprietary machine learning algorithm MatrixNet was developed by Yandex, becoming one of the key components that Zen functions on. The first Yandex service to introduce the use of recommendation technology was Yandex.Music, which was launched in September 2014. This technology was then implemented in Yandex.Market and Yandex.Radio.

In June 2015, a beta version of Zen became available. At first, the Zen content feed showed only content from the media, and the service was only available to the 5% of users of Yandex Browser on Android that had registered a Yandex account. Prior to this, Zen was available in an experimental form on the webpage zen.yandex.ru.

In the following months, other types of content were added to Zen, such as image galleries, articles, blogs, forums, videos from YouTube, etc.

According to data from April 2017, Zen is available in more than 50 languages in more than 100 countries, including the United States, India and Brazil.



                                     

4. Finances

Zen is one of Yandexs experimental business activities. According to data from 2015, this segment earned the company almost half a billion rubles in revenue. In Q2 2016, Zen and other experimental services brought in 153 million rubles in revenue to Yandex.Monetization of the service is due to ad blocks built into the news feeds in Russia, ads are served by Yandex.Direct.

                                     

5. Competitors

After the release of Zen, several major companies also announced personal recommendation services. In May 2016, Mail.Ru Group presented a similar project called Likemore, which offers users content from VK VKontakte social media groups. In August 2016, Google launched a test version of a similar service that recommends news articles. Apple and Facebook have also launched news services with similar functionality.