The 10 brands ChatGPT mentions most. 6 of them have nothing in common.
We ran 12,400 buyer-intent prompts and tallied every brand mention. The leaderboard is weirder than you think — and the patterns inside it are weirder still.
We pulled together 12,400 distinct buyer-intent prompts across 40 categories — SaaS, ecommerce, B2B services, consumer tech, fintech — and ran them through ChatGPT (gpt-5, web-search enabled) over the course of two weeks. Every brand mentioned in every response was tagged and counted. The resulting leaderboard has 10 names at the top. Some you'd expect. Most you wouldn't.
The top 10
- Google (mentioned in 23.1% of responses)
- Microsoft (18.4%)
- Apple (14.7%)
- Notion (12.2%)
- HubSpot (11.8%)
- Shopify (10.6%)
- Stripe (10.1%)
- Salesforce (9.8%)
- Wikipedia (9.3%)
- Amazon (8.9%)
The four obvious ones
Google, Microsoft, Apple, and Amazon dominate everything. They're mentioned across every category, often as the implicit default ("like Google's…") or as the comparison point ("unlike Apple…"). This is the AI-search equivalent of being the brand in the dictionary.
The six that don't fit
The interesting names are 4-9. Notion, HubSpot, Shopify, Stripe, Salesforce, Wikipedia. What do they have in common? On the surface, nothing — productivity tool, CRM, ecommerce platform, payments infra, enterprise CRM, encyclopedia. Different categories, different ages, different ICPs.
But dig in and a pattern emerges: all six are the canonical example of their category. When ChatGPT needs to explain what a CRM is, it reaches for HubSpot or Salesforce. When it needs to explain payments, Stripe. When it needs to explain a knowledge base, Notion or Wikipedia. They're not just well-known brands — they're how the model defines the category itself.
Being category-canonical isn't a marketing position. It's a topological position in the model's representation of your industry.
The implication for your brand
Optimizing to be "mentioned" is the wrong target. Optimizing to be the canonical example of a specific concept — even a narrow one — is what gets you persistently into the top of LLM recommendations.
Written by
Lena Park
Co-founder & Head of Research
Built the AI Visibility engine. Spends too much time reading model release notes and yelling about prompt drift.
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