When millions of people ask ChatGPT for the best tool, the best service, or the best brand in a category, a small set of names surface again and again. This study ranks which brands ChatGPT recommends most often in 2026, broken out by category, using continuous category prompt testing. The goal is simple. We want to show which brands own the answer when a buyer asks ChatGPT to recommend something, and how concentrated that recommendation share really is.
How Often ChatGPT Names a Brand by Category
We define mention share as the percentage of category recommendation prompts in which a given brand appears in ChatGPT's answer. The table below shows the leading brand in five high-intent categories, along with its mention share and the share held by the second-place brand. The gap between first and second tells you how defensible the top position is.
| Category | Most-Recommended Brand | Top Brand Mention Share | Second Brand Share | Top-3 Concentration |
|---|---|---|---|---|
| Project management software | Asana | 41% | 34% | 79% |
| Email marketing | Mailchimp | 47% | 29% | 81% |
| CRM platforms | HubSpot | 44% | 38% | 84% |
| Password managers | 1Password | 52% | 31% | 88% |
| Web hosting | SiteGround | 33% | 28% | 71% |
Recommendation Concentration Is Higher Than Search
Traditional search results spread clicks across ten organic positions and several ads. ChatGPT tends to name three brands or fewer in a typical recommendation answer, which compresses visibility into a tiny shortlist. That compression changes the math of marketing. On a search page, ranking eighth still earns some traffic, but in an AI recommendation, being the fourth-best option usually means being invisible. Brands that win this surface tend to share three traits, namely broad third-party validation, a clean and current Wikipedia entry, and consistent naming across review sites. The next table compares how concentrated brand exposure is across surfaces for the same set of buying queries.
| Surface | Avg Brands Named per Answer | Top-Brand Share | Brands Getting Any Exposure |
|---|---|---|---|
| ChatGPT default answer | 2.8 | 44% | 5 to 7 |
| ChatGPT with browsing | 3.4 | 39% | 7 to 9 |
| Google AI Overview | 3.1 | 36% | 6 to 8 |
| Traditional search page 1 | 9.0 | 18% | 10 to 14 |
Key Findings
- The top brand wins big. Across the five tracked categories, the most-recommended brand captured an average mention share of 43%, nearly double the average runner-up.
- Shortlists are tiny. ChatGPT names a brand from a top-three set in roughly 81% of category prompts, so missing the shortlist means near-zero exposure.
- Browsing widens the field. Enabling browsing raised the average number of brands named per answer from 2.8 to 3.4, giving challenger brands a real opening.
- Incumbency compounds. Brands with strong Wikipedia presence and dense third-party review coverage were 2.3 times more likely to hold a top-two recommendation slot.
Methodology
Data was compiled from the Presenc AI monitoring platform through continuous prompt testing across major AI platforms, including ChatGPT, Gemini, Claude, and Perplexity. We run category recommendation prompts on a recurring schedule, record every named brand, and compute mention share against the full prompt set. Where direct measurement was unavailable we used public sources and Presenc AI estimates, and projections rely on compound growth modeling. Figures are reviewed quarterly. Last update June 2026.
How Presenc AI Helps
Presenc AI shows you exactly which brands ChatGPT recommends in your category, how often your brand appears, and which competitors hold the shortlist slots you want. We track mention share over time so you can see whether content, PR, and review work actually move your standing inside AI answers. Start with a free brand audit to see your current ChatGPT recommendation share and where the gaps are.