Read in
Customer reviews are becoming a key ranking signal in AI search, influencing how platforms like ChatGPT and Google AI Overviews recommend brands. And AI search is impacting every aspect of the digital customer journey—from brand discovery to research and even purchase—as overviews and generative search results provide faster answers.
In a 2025 report, 80% of people relied on AI summaries at least 40% of the time, indicating a 15–25% reduction in organic web traffic. 1 Studies have also found that web traffic from AI search resulted in shoppers spending 32% longer on-site, bouncing 27% less and converting to purchase 31% better than organic traffic during the 2025 holiday season. 2
A big part of this shift is that nearly all AI search engines rely on customer reviews along with accurate product information and more to guide results. The weight of importance that reviews impact results depends on the large language model (LLM) like Gemini, Claude or ChatGPT. 2026 is a key opportunity for brands to boost their AI trust and credibility scores through customer reviews.
In this blog article, we will explore how reviews impact search today and the best strategies to build reviews to promote AI search referrals.
The lasting impact of reviews on AI search or AEO
While the goal for any brand should be growing the number of positive reviews, bad reviews can be just as important when it comes to making a brand seem trustworthy. Brands without any negative reviews, or worse, those caught manipulating or deleting bad reviews open themselves to enforcement by the FTC, Google, Amazon and more. The key is maintaining a strong review average and not letting this score slide down.
Here are some of the top ways reviews impact AI search:
- Tone: Limited reviews make it more difficult for AI models to associate an overall customer sentiment across products or services, making recommendation less likely
- Future (training) impact: LLM AI search engines utilize training data to improve efficiencies, including vast amounts of online data; aggregated reviews have the potential to create a reputational echo in AI responses for months or years to come
- SEO boost:As customer reviews increase, so too does traditional SEO ranking, feeding another critical component of credibility that impacts AI search 3
- Local visibility: Google’s Help Center states that more reviews as well as positive reviews can help local rankings and provide greater geographic visibility in AI search recommendations
Reviews are the language of brand experience. Consider turning common phrases, issues, and recommendation discussion into content for FAQs, comparison pages and product listing pages to create consistency. Incorporating review language throughout the site or store helps both thorough customers that prefer to research their purchases and AI generative search engines understand the brand better.
Building a successful review strategy for AI search
AI summaries, overviews and generative prompts pull from a variety of sources, including website content, external blogs, connected social content and more. A strategy that incorporates building and maintaining reviews is an opportunity for expanding brand discovery.
1. Pairing reviews with products: Ensure product data and corresponding reviews are paired correctly within Google Merchant Center to help build product and store ratings alongside existing Google Customer Reviews. For ChatGPT shopping, ensure the product data feed file is updated, including images, titles, stock levels and more for AI to reference.
2. Updated Google Business Profile: Review all information to ensure it is correct and updated. Consider providing a shortened review link or QR code on receipts, emails, and end-of-chat prompts, but do not incentivize reviews.
3. Convert reviews into marketing: Feature common review language in ads, social media and email marketing efforts. Verified reviews across multiple platforms like Google Store rankings or Amazon Ratings can improve trust and impact purchase decisions for AI and shoppers when included in marketing content.
4. Track reviews as a KPI: Monitoring new feedback, responding to both positive and negative feedback and connecting reviews with the user experience are all critical to delivering consistent review aggregated rankings.
Reviews are just one factor that AI search engines utilize to recommend or summarize a search. They also consider awards, accreditations, affiliations, authoritative content and Google Website Authority. Making it easier to find out what existing customers have to say about your brand goes a long way to helping new shoppers trust and move forward with confidence.
At Trone, we can help you optimize your review content strategy while improving visibility for new and recurring shoppers while building trust and authority for AI search engines. Contact us to discuss your marketing goals and how reviews can help your brand gain momentum as AI search engines continue to shape how we discover recommended products and services.
Sources:
