Megamarket has updated the main page and navigation — they have become personalized

«Megamarket» has updated the appearance of the main screen in the application. Now the marketplace offers improved navigation and personalized content — selections of products and materials created based on analysis of user behavior.

Megamarket has updated details of its interface — the main page and navigation. Now the first positions show the products and collections that are most interesting to the user. Also on the site, interesting articles on the topic are now available that will help inspire you to learn something new.

Personalized ranking on the main page is based on accumulated data on user behavior on Megamarket and a number of specified business rules. It is based on the marketplace’s own ML algorithms.

“We believe that Megamarket is more than just a marketplace. We have a huge number of opportunities to help people set and achieve life goals, discover something new and interesting. We strive to become one of the most personalized marketplaces to make using Megamarket even more convenient. Now both in the feed and in marketing selections, products will be ranked depending on the user’s interest in them, as well as the likelihood of purchase. This solution will appeal not only to buyers, but also to sellers, because now it will become even easier to find your audience and promote products — regardless of the category,” shares Igor Rozhkov, Marketing Director of Megamarket.

Updated navigation allows you not only to simplify the search for products on the site, but also to anticipate the needs of customers. This approach allows you to effectively and natively promote those products that are interesting to a specific person. In addition, the interface takes into account that customers may have different entry points and paths in different product categories. Therefore, for each category, Megamarket specialists built a unique user path.

Also, Megamarket previously announced the ability to find your favorite clothes, shoes and accessories on the site based on photographs. Users can upload both photographs of individual items and an entire image — the neural network will select the most similar products and offer them in a list. According to testing data, the accuracy of the technology reaches 98%.

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