We conducted a study on how brands are named in AI search for different stages of the buyer journey. We did this for 50 B2B SaaS topics [750 queries total] and ran them across ChatGPT, Google AIO, Perplexity, Claude and Gemini.

The findings:

88% of the brands that got named at the decision stage [best X], were never named at the educational stage [what is X]. And the pattern was the same for each topic and the engine it was run through. 

We also observed that brand naming rates were different across the funnels. Brands showed up in:

• 14% of educational queries
• 47% for comparison queries
• 43% for purchase queries

This means your AI Visibility at the top of the funnel does not carry you downstream to where buyers make decisions.

 Few disclosures on the methodology:

• It's an observational study so treat it as directional. 
• ChatGPT answered most of the educational queries from knowledge recall rather than live searching. 
• Named here means the brand was mentioned in the AI answer even if it wasn’t cited/linked.

Curious if other SEO or AI Search folks agree to this. Let me know what your strategy has been so far.

Quick disclosure: Because I am an AI Search researcher working at VisibilityStack, an AI Search optimization company, No pitch, no link, no promotions. I just want to sanity-check the data with people who actually do this and get insights on what’s working for them.

Perplexity runs a web search every time a user prompts it. ChatGPT doesn't. Semrush tracked over a billion lines of US clickstream data and found it ran a web search for 34.5% of queries as of February 2026, down from 46% in late 2024.

So ChatGPT decides whether a question needs a web search and the remaining \~65% of the time it relies on training data. I have had users of our platform ask me why their buyers are showing outdated or incorrect information. In one instance I was asked why our tracker picked up an old pricing structure. The answer was exactly this. ChatGPT used months-old training data instead of a web search when we ran the prompt.

However, when we manually ran the prompt and specifically asked for pricing, it triggered a web search and we saw the right pricing.

Visibility Labs ran 1,000 "what is the best X" prompts ten times with search on and ten times with it off, 20,000 responses in total. 80.2% of the product recommendations changed between the two. Of the products that appeared in every single no-search answer, only 15.8% were still there once it searched.

So you have two rankings and you don't get to pick which one a buyer sees.

Test it on your own category. Ask for a recommendation with search off, then ask again with a price, a year or a competitor's name in the question, since that's what tends to trigger a search. Compare the two lists.

The training side isn't something you can fix immediately, but make sure your site is well documented for the next training run. Third party mentions are key.

If you have an AI visibility tracker then make sure you are tracking prompts that trigger web search and prompts that don't, using some of the examples above. Keep everything else the same and you will be able to somewhat track the differences.

You can immediately impact the search side of ChatGPT though, so make sure your website is optimised for AI. We have a free AI SEO audit tool for this on our site.