Most Russians Prefer E-Commerce Sites Over Search Engines for Product Searches

Most Russians now search for products directly on e-commerce platforms rather than using traditional search engines. A study by Avito Advertising surveyed 10,000 people and found that 90% prefer classifieds sites and marketplaces, while only 25% use search engines for product searches.

E-Commerce Dominates Product Searches

According to the study, 79% of respondents visit classifieds sites and marketplaces when they want to buy something. Additionally, 57% use these platforms to compare options, and 33% rely on them for reading reviews.

Social networks and online stores also play a role in product searches. The study found that 19% of Russians look for products directly on retailer websites, while 9% use social media.

Changing Search Behavior

Yakov Peysakhzon, director of Avito Advertising, noted that online search behavior is shifting. More users now turn to e-commerce platforms for product searches instead of traditional search engines. He explained that this trend aligns with global patterns, as even major IT companies have reported a drop in search engine traffic. The convenience of e-commerce search functions is a key reason for this shift.

Shopping Habits and Advertising Influence

Many Russians actively use e-commerce search features, with one-third of respondents adding products to their “Favorites” lists several times a week. On average, users save products about seven times per month.

The most searched product categories on e-commerce platforms include:

  • Clothing and footwear (62%)
  • Gifts (46%)
  • Beauty products (45%)

Advertising on e-commerce platforms also influences purchasing decisions. About 25% of respondents said that marketplace ads helped them with their most recent purchase. By comparison, ads on social media (19%), television (16%), and search engines (15%) had a similar but slightly lower impact.

Growing Demand for IT Services

This study follows a previous Avito report, which found that demand for IT services in Russia increased by 241% in 2024 compared to the previous year.

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.