Yandex Enhances Product Display in Search Results

Posted by By Dan Taylor 2 Min Read

Yandex has revamped how store products are displayed in its search results, aiming to streamline the shopping experience for users. The new layout presents products in a unified format and single column in desktop search results, making it easier for users to compare offers from different sellers.

The updated “Prices in stores” block is now integrated directly into the main search results, appearing between the first and fourth positions. This block features three product listings, each accompanied by an image and description. This native integration ensures that crucial information such as product characteristics, advantages, and reviews are readily accessible to users, aiding in informed purchase decisions.

Image Credit: https://webmaster.yandex.ru/blog/novyy-format-otobrazheniya-tovarov-magazinov-v-poiske

For sellers, inclusion in the “Prices in stores” block requires transmitting accurate images, descriptions, and prices in the YML feed. Those not yet compliant with these requirements need to update their feeds to meet the necessary standards.

This update reflects Yandex’s ongoing efforts to enhance user experience and support sellers. By providing a more intuitive and informative product display, Yandex aims to simplify the shopping process and improve visibility for store products.

This initiative is part of Yandex’s broader strategy to leverage its technological advancements, including its recently released open-source library for accelerating neural network training.

Source: Yandex Blog

Dan Taylor
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Dan Taylor is the founder and editor of International Search Insights (ISI), the publication behind ReadIsi, and a Partner and Head of Innovation (Search & AI) at SALT.agency. He has worked in search for more than a decade, in-house and agency-side, and is regarded as one of the West’s leading voices on search engines beyond Google, including Yandex, Baidu, Naver and Cốc Cốc. On ReadIsi, Dan covers the engines and AI answer platforms that English-language coverage tends to miss: Baidu and ERNIE, Yandex and Alice AI, Naver, Cốc Cốc, Shenma, Sogou, WeChat and Weibo search, plus DeepSeek and Alibaba’s Qwen. He also keeps dated records of documented changes, such as the Yandex, Baidu and Naver algorithm update histories and the DeepSeek, ERNIE and Qwen model update histories. His approach is to take learnings from global search engines and apply logic with a high evidence threshold. A claim needs a source, patterns seen in one market are treated as a hypothesis until they are checked in another, and where the evidence is thin he says so. For brands, that means advice built on what can be shown, with measurement that separates being cited from being chosen. Dan is credited with coining the term “edge SEO” and won the inaugural TechSEO Boost research competition in 2018 for his work on CDN and edge changes for SEO. In 2026 he was credited with coining “Infinite Tail” to describe how keyword research is changing with AI search. He is the author of AI Search Marketing For The Travel Sector, writes for Search Engine Journal, Search Engine Land and Travel Marketing Guy, and has advised technology, SaaS, travel and enterprise ecommerce brands, including Cloudflare, GitLab and Airbnb. He has given multiple talks and panels at the International Search Summit in Barcelona, and has also spoken at Optimization Moscow, brightonSEO, Google Search Central Live Deep Dive Asia in Bangkok, Athens SEO and the Asia SEO Virtual Summit 2026, where his talk looked at how Baidu, Naver, DeepSeek, Tencent, Cốc Cốc and Yandex built their own AI answers.
Founder & Editor