Consumers Increasingly Depend on Reviews as Brand Strength Declines, Study Finds

A new study by Ashmanov and Partners reveals a rising reliance on online reviews, particularly among female, younger, and lower-income consumers, as weaker brands drive demand for third-party opinions.

A new study by Ashmanov and Partners reveals a rising reliance on online reviews, particularly among female, younger, and lower-income consumers, as weaker brands drive demand for third-party opinions.

According to Ashmanov and Partners, a lack of strong branding and limited product information has led more buyers to rely on reviews. Consumers see reviews as a trusted source, with 55% of buyers feeling reviews often reflect reality and 41% noting they occasionally do. Only a small minority, 3%, reported complete distrust in reviews.

The survey found that nearly a third of consumers trust reviews more now than before, while 40% of those reading reviews frequently say their trust has grown. Just 12% of respondents expressed reduced trust in reviews, and only 5% encountered highly unreliable reviews.

Consumer Motivations for Reading Reviews

Consumers are turning to reviews in response to weaker product branding and information sources, according to Anton Trishin, Head of Research and Analytics at Ashmanov & Partners. He explained that reviews provide a sense of guidance and reassurance in uncertain purchase situations, especially when product information is minimal or from lesser-known brands.

Customers most often read reviews under three circumstances:

  1. When buying a product for the first time.
  2. If the product comes from a less recognized manufacturer.
  3. When the product description lacks detail.

These motivations are largely tied to avoiding mistakes (56%), learning from other buyers’ experiences (54%), and compensating for a lack of detailed product information (46%).

The research found two primary consumer behaviors:

  • Reviews act as a driver for purchase when official information or advertising is sparse (41%).
  • Advertising and detailed product information can substitute for reviews in purchasing decisions (34%).

Factors Driving Positive and Negative Reviews

Ashmanov and Partners also examined the triggers for leaving reviews. The study revealed that most buyers (73%) share reviews after making a purchase. Negative reviews are generally motivated by the desire to caution other buyers, particularly when customers experience recurring issues or fail to resolve problems directly with the company.

Secondary reasons for negative reviews include unmet advertising expectations (35%), worsened purchase conditions (24%), wrong product choice (22%), and price increases (17%).

Positive reviews, meanwhile, are more likely when consumers are highly satisfied (72%) or wish to share their experience with others (63%). Ease of writing a review (49%) also contributes to positive feedback, whereas incentives like discounts or bonuses influence only 30% of reviewers. However, requests alone, such as reminders from companies to leave reviews, generate a low response rate (18%).

Convenience in Review Requests

The study also examined the methods companies use to request reviews. Mobile app notifications are the most preferred, with 47% of respondents favoring this method. Email and purchase-included leaflets tied for second at 38%, while requests via messaging apps are also acceptable to many consumers (36%).

Less favorable methods include social media requests and SMS, seen as convenient by only 28% and 27% of respondents, respectively. The least convenient, according to buyers, is using a QR code at checkout, with just 16% finding this method easy.

Insights and Future Implications

The study by Ashmanov and Partners highlights the growing importance of online reviews as consumers increasingly rely on peer opinions over weaker brand identities. For companies, prioritizing product quality, managing customer relations, and encouraging honest feedback are crucial for maintaining a positive presence in today’s review-driven market.

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.