Ozon Introduces New Feature to Follow User Reviews

Posted by By Dan Taylor 2 Min Read

Ozon has launched a new feature called “Public Profile” in its app, allowing users to follow other customers and read their reviews. This feature enables buyers to subscribe to profiles of individuals whose purchases align with their own interests, provided the profile is open.

With this update, users can explore the opinions of others on products they are curious about and check out reviews for additional items. If a user finds a particular review helpful, they can follow the author and discover their thoughts on other products.

Ozon explained that many people already share their shopping experiences on social media. This feature is designed to replicate that behavior on the platform, making it easier for users to share and discover product recommendations within the app itself.

Public profiles will display a user’s first name and the initial of their last name, along with their non-anonymous reviews. However, reviews for certain products, such as those in the 18+ category, will remain hidden. Users also have control over their privacy settings—they can choose to hide their entire public profile, keep specific reviews private, or modify their display name.

This development follows Ozon’s recent financial report for the second quarter, where the company announced a 30% revenue increase compared to the previous year, reaching 122.5 billion rubles.

Source: Ozon HQ Telegram channel

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