Which LLMs Should Brands Monitor for AI Visibility: ChatGPT, Gemini, Claude, Perplexity, or DeepSeek?

How big is each platform?

The main public figures, from different sources and methods, so compare them with care:

In the US, Pew found in early 2026 that 44% of adults had used ChatGPT and 24% Gemini. Referral traffic tells a different story again. In SE Ranking's June 2026 study of website traffic, ChatGPT sent about 75% of AI referrals, Gemini 12%, Perplexity 7%, Copilot 4% and Claude 3%. Perplexity sends far more visits than its user share suggests: about 7% of AI referrals from a far smaller share of chatbot users.

Does tracking Gemini and Claude increase AI search reach compared with tracking only ChatGPT?

It increases the share of the audience your measurement covers, and often the number of problems it finds. Tracking only ChatGPT covers about half of chatbot web visits. Adding Gemini and Claude takes that to roughly 91%, before counting Google's AI Overviews and AI Mode.

The bigger reason is that the engines look in different places:

• ChatGPT search uses OpenAI's own crawler and index plus third-party search providers. Studies disagree on how closely its citations follow Bing: Seer found 87% matched Bing's top 20 for the same question, while Ahrefs found only about 8% overlap with Bing's top 10, similar to Google's.
• Gemini, AI Overviews and AI Mode draw on Google's index.
• Claude relies on Brave Search. In one analysis of about 35,000 Claude citations, 79% of cited pages ranked in Brave's top 10, against 34% in Google's.

So a brand can be well placed in Google's AI features and absent from Claude, because Brave does not index its key pages, or cites different reviews. Tracking only ChatGPT would miss both problems. That said, visibility is correlated across assistants. Ahrefs found a strong overlap in which brands different assistants mention, so tracking more engines tends to add fixes rather than overturn the picture.

How many AI platforms should an AI visibility audit cover?

An audit is a one-off snapshot, so it should be broad. Cover five or six surfaces, grouped by the index behind them:

1. ChatGPT, for the largest chatbot audience and its own mix of sources.
2. Google AI Overviews, for the largest overall audience.
3. Google AI Mode or Gemini, for Google's conversational surfaces.
4. Claude, for the Brave-based index and business users.
5. Perplexity, for referral traffic that is large relative to its share of users.
6. Copilot, if your buyers work in Microsoft environments.

Run the same 20 to 50 buyer questions on each. The audit tells you where you are strong, where you are missing, and which engines behave differently enough to need their own tracking. A method for choosing those questions is in what buyer questions to test across ChatGPT, Perplexity, Gemini and AI Overviews.

How many AI models should you track for AI visibility?

For ongoing tracking, three or four is the practical range for most brands. Beyond that, cost rises in proportion while insight rises slowly. Tracking cost is roughly prompts × engines × runs. For example, 100 prompts on four engines daily is about 12,000 answers a month; on eight engines it is 24,000.

Choose the three or four by two rules:

• Audience: the engines your buyers use, from customer questions and your analytics referrals.
• Index diversity: at least one Google surface, ChatGPT and, if relevant, Claude, whose search draws on Brave. Engines sharing an index often produce similar results, so tracking two Google surfaces adds less than adding Claude.

Rerun a broad audit once or twice a year to check whether a new engine has become important. Comparing results across engines fairly is covered in how to normalise visibility scores across ChatGPT, Perplexity, Gemini and Claude.

Which AI search engines should businesses prioritize for visibility?

It depends on the business:

DeepSeek has about 4% of worldwide chatbot web visits, more than Perplexity, but check its usage in your own markets before adding it. For most brands selling in Europe and North America, it is a lower priority than Claude or Perplexity.

Should we optimize for ChatGPT or Google AI Mode first?

Most of the work is the same for both: pages that answer questions clearly, content that crawlers can read without JavaScript, and a strong presence on the review sites and lists that answers cite. Start there. The differences come after:

• Google AI Mode draws on Google's index. If your pages already rank in Google, you start ahead. Its audience is very large, with more than a billion monthly users.
• ChatGPT leans on its own index, other search providers and third-party lists and reviews. Check that your key pages are indexed in Bing as well as Google, and that the comparison articles ChatGPT cites include you.

A useful rule is to start where your buyers are and you are weakest. If you rank well in Google but rarely appear in ChatGPT, ChatGPT is the bigger opportunity. If you are new and have little search presence, Google fundamentals come first, because AI Mode and AI Overviews both depend on them.

What might a sensible set-up look like?

Consider an illustrative B2B payroll company, Pelvarrow. Its audit of 30 questions across six engines found it named in 40% of ChatGPT answers, 35% of AI Overviews, 10% of Claude answers and 30% of Perplexity answers. Claude cited two review sites that did not list Pelvarrow, and Brave did not show its pricing page. Pelvarrow chose four engines for daily tracking: ChatGPT, AI Overviews, Claude and Perplexity. It fixed its Brave indexing and approached the two review sites first, because that gap was the largest.

What do people ask about which LLMs to monitor?

Is ChatGPT enough?

Rarely. It covers about half of chatbot web visits, and none of Google's AI Overviews or AI Mode audience.

Should we track DeepSeek?

Only if your buyers use it. Check its usage in your markets first.

Is Perplexity worth tracking with a small user share?

Often yes, because it sends a large share of AI referral traffic relative to its size.

How often should we re-check which engines to track?

Run a broad audit once or twice a year, or when a new engine starts appearing in your referral data.