When people ask ChatGPT where to buy something, one name appears far more often than any other: Walmart. In Ahrefs’ analysis of 5,516,381 U.S. ChatGPT answers from November 2026, Walmart was mentioned in 95,605 responses — roughly 1.73% of the indexed replies. That single statistic underlines a clear pattern: the kinds of queries users send to AI assistants heavily shape which brands get recommended.

Key findings at a glance

Ahrefs’ Brand Radar lists the 100 most-mentioned commercial brands in ChatGPT answers. The top 10 by mentions are:

  • Walmart — 95,605 mentions (1.73%)
  • Target — 52,096 (0.94%)
  • Apple — 45,297 (0.82%)
  • Amazon — 38,795 (0.70%)
  • The Home Depot — 34,876 (0.63%)
  • Nike — 33,327 (0.60%)
  • Google — 30,775 (0.56%)
  • Toyota — 30,261 (0.55%)
  • Costco — 29,186 (0.53%)
  • Best Buy — 24,746 (0.45%)

Retailers are especially prominent: 23 of the top 100 brands are retailers, accounting for 35% of mentions in the list. Automakers follow, with 15 car brands contributing about 14% of mentions. Ahrefs’ analysis also shows a pattern by query intent: shopping and price-comparison questions mainly name stores, while ownership, troubleshooting and how-to queries tend to name product manufacturers.

Why these patterns emerge

The distribution reflects what people ask AI assistants. Transactional queries — “Where can I buy X cheaply?” or “Which store has Y in stock?” — naturally yield retailer names. Automotive queries about reliability, resale value and model comparisons generate direct brand references, which helps explain the strong presence of carmakers.

Some brands appear for different reasons. Google is usually cited in functional or how-to contexts (Translate, account help, Pixel phones) rather than as a shopping destination. Amazon shows up both as a marketplace and as a family of services (Prime Video, AWS, Kindle), so it captures mentions across multiple query types.

Practical takeaways for marketers and product teams

For teams tracking brand visibility in AI assistants, the Ahrefs data suggests three pragmatic steps:

  • Measure AI share of voice. Treat assistant mentions as a distinct channel. Monitor which assistants name your brand, in which queries, and alongside which competitors.
  • Optimize the pages assistants cite. Ahrefs reports the pages ChatGPT cites. Prioritize product pages, pricing information, inventory indicators and concise FAQs that answer common user questions directly — these are the formats retrieval systems favor.
  • Map content to intent clusters. Build price, stock and comparison content for retailer-style queries; focus on specifications, troubleshooting and official how-tos for product brands.

These are starting points, not guarantees. Whether an assistant cites your brand depends on its training data, retrieval sources and any editorial filters the platform applies.

Limits of the data and what to monitor

Ahrefs is clear about the dataset’s scope: it covers U.S. ChatGPT answers from November 2026, excludes non-commercial entities and merges variant names for the same brand. That makes the findings a useful snapshot for that context, but not a global or cross-platform claim.

Marketers should therefore treat this as directional intelligence. Practical next steps are to set up routine monitoring of AI-driven mentions across multiple assistants, identify the specific pages those assistants cite, and close content or technical gaps that stop your brand from being surfaced. Small changes in indexing, source trust or citation rules on an assistant can materially alter which brands get recommended.

What to watch next

Watch whether these mention patterns hold across other assistants and regions, and track any platform-level changes to citation or retrieval policies. Brands that begin measuring AI share of voice and aligning content to likely query intents will be better placed to influence how assistants recommend them — and to convert the attention those recommendations bring.