Yandex’s Product Search Update Insights From Optimization 2024

Experts Discuss Challenges in Product Availability and Search Reliability.

Experts Discuss Challenges in Product Availability and Search Reliability.

During the Optimization 2024 conference, panelists explored Yandex’s latest updates to product search functionality. A key focus was on the platform’s improved ability to detect product availability and delivery feasibility, as well as the challenges posed by dishonest practices in competitive markets.

Accuracy in Product Availability

An audience member raised concerns about the implications of Yandex’s new update, particularly for B2B markets. For industries like industrial equipment manufacturing, products are often made to order and may require months for delivery. This creates a disparity with competitors who may misrepresent availability to attract customers.

Mikhail Slivinsky of Yandex acknowledged the complexity of the issue, noting that competition is often shaped by the specific market context. Businesses producing custom equipment are typically judged against similar providers, not retailers offering instant delivery.

Slivinsky also highlighted that user trust and feedback play a significant role in shaping search outcomes. Sites that mislead customers may gain short-term visibility, but their reputation and customer loyalty ultimately suffer.

Mitigating Errors in Search Rankings

Slivinsky expressed confidence in Yandex’s ability to minimize errors in handling product availability information. He outlined several factors contributing to the platform’s accuracy:

  1. Advanced Subsystems: Yandex employs multiple subsystems to cross-check and validate product data. These systems aim to filter out misleading claims and prioritize trustworthy sites.
  2. User Feedback: Customer responses to dishonest practices influence rankings over time, helping to organically regulate the search ecosystem.

Slivinsky invited users to report specific cases of unscrupulous sites achieving undue prominence in search results. This feedback helps Yandex refine its algorithms and address gaps in detection.

Competing on Trust and Transparency

The panel emphasized that businesses operating transparently and valuing customer trust are better positioned for long-term success. While dishonest practices may yield temporary gains, they risk damaging brand loyalty and search visibility.

Key Takeaways

  • Context Matters: Yandex evaluates product availability within the specific competitive environment of each market.
  • Trust Over Tactics: Businesses that prioritize honest practices are more likely to maintain user trust and achieve sustainable growth.
  • Continuous Improvement: Yandex relies on advanced systems and user feedback to enhance its product search capabilities and minimize errors.

The discussion underscored the importance of transparency in product availability and the role of user trust in maintaining a fair and reliable search ecosystem. For businesses, investing in reputation and accuracy remains a critical strategy in navigating competitive online markets.

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.