Does ChatGPT Recommend Brands? What We Found

Yes, ChatGPT recommends brands. When users ask product or service recommendation questions, ChatGPT generates responses that name specific companies, compare options, and often highlight pros and cons. This is not a theoretical capability. It happens millions of times per day. Learn how to check if ChatGPT mentions your brand.

We tested 200 product and service recommendation prompts across 12 industries to understand how ChatGPT selects which brands to mention. Here is what the data shows.

ChatGPT Names Brands in 87% of Recommendation Queries

Of the 200 recommendation prompts we tested (e.g., "best CRM for startups," "top web hosting providers," "recommended project management tools"), ChatGPT named at least one specific brand in 87% of responses. The average response mentioned 4.3 brands.

The remaining 13% produced generic advice without naming specific products, typically for highly niche or ambiguous queries.

What Determines Which Brands Get Recommended

Our analysis identified three primary factors that correlate with ChatGPT brand inclusion:

1. Web Presence Volume

Brands with more indexed pages, more third-party reviews, and more mentions on authoritative sites were recommended more frequently. The top-recommended brand in each category averaged 3.2x more third-party mentions than the least-recommended competitor.

2. Structured Content Quality

Brands whose websites included clear product descriptions, comparison pages, FAQ sections, and schema markup appeared more consistently. ChatGPT's web search feature pulls from structured content, and the base model was trained on well-formatted web pages.

3. Review and Comparison Presence

Brands that appeared frequently on review sites (G2, Capterra, Trustpilot) and in comparison articles were recommended at higher rates. These third-party sources serve as validation signals that increase AI confidence in recommending a brand.

Smaller Brands Can Compete

One notable finding: brand size alone did not determine recommendation frequency. In 34% of categories, at least one brand with fewer than 500 employees appeared in the top three recommendations. Smaller brands that had strong niche authority, clear product differentiation, and well-structured websites outperformed larger competitors with weaker AI-facing content.

Web Search vs. Base Model

ChatGPT behaves differently depending on whether web search is enabled:

• Without web search - Recommendations are based on training data. Established brands with large historical web footprints dominate. Newer brands or recent product launches may be absent.
• With web search - Recommendations incorporate real-time data from the web. This levels the playing field somewhat, as current reviews, articles, and product pages influence the response.

The trend is toward more web-search-powered responses, which means your current web presence matters more than ever.

What This Means for Your Brand

If ChatGPT is recommending your competitors but not you, the problem is likely one of visibility rather than product quality. AI recommendation engines can only cite what they can find and verify.

The most effective actions to increase your brand's recommendation likelihood:

• Ensure AI crawlers can access your site by checking robots.txt for GPTBot access
• Publish an llms.txt file that summarizes your brand and products for AI crawlers
• Implement schema markup (Organization, Product, FAQ) to help AI engines understand your offerings
• Build third-party presence on review sites, directories, and authoritative publications
• Create comparison content that positions your brand alongside competitors

Monitor Your AI Recommendations

AI recommendations are not static. They shift as models update, new web content is indexed, and competitor actions change the landscape. Regular monitoring with tools like Prominara lets you track which prompts mention your brand, how sentiment changes, and where gaps exist compared to competitors.

The brands that treat AI visibility as an ongoing channel rather than a one-time check will capture a disproportionate share of the growing AI recommendation traffic.