What AI Actually Says About Your Brand When Nobody Is Watching

We ask the engines what they know about a brand from training data alone, then compare it to what the brand's own site says. The gap is the problem. Ask ChatGPT about your brand while logged into your own account and you get a flattering answer. It has your history, your phrasing, your context. It is the best version of your brand you will ever see, and it is not the one your buyers get. LLM Perception exists to see the other version.

5 min read

Comparison Content

The step

We query the engines about a brand from training data alone — no web access, no help. Then we compare each answer against what the brand's own homepage actually says.

The gap between those two things is the entire finding. It is where a model has invented a feature, aged out a price, attached the wrong founder story, or quietly recommended a competitor instead.

What the score is made of

One Brand AI Visibility Score out of 100, blended from three components, each scored 0–100:

  • Recognition — 30%. Do the engines know the brand exists from training data alone?

  • Accuracy — 30%. When they describe it, how right are they? Every hallucination costs here.

  • Positioning — 40%. Does the brand surface on category and industry queries, or does the model reach for a competitor?

Positioning carries the most weight because it is the one that costs money. A model can know exactly who you are and still hand the buyer to someone else.

The finding that lands hardest

A heritage leather goods brand — decades of trading, a real catalogue, a name their customers know. Asked cold, Claude offered that it might be a whiskey company. Possibly a restaurant.

Not a wrong detail. No recognition at all.

That is what a score in the low 40s looks like from the inside, and it is why we start here rather than with content.

Why it decides everything downstream

There is no point optimising content for engines that do not know who you are. Identity comes first, and this is how we find out whether it exists.

What we found across 900 brands

We ran this at scale. The average score was 46 out of 100. 22% scored under 30. 53% scored under 50.

The number that surprised us: brands doing $20M+ averaged 46.1 against 46.0 for smaller brands. Size buys you nothing here. A twenty-year-old catalogue and a large marketing budget do not make a model understand what you sell.

The proprietary part

The batch version runs against hundreds of brands at once, which is what made that study possible — and what makes it useful in a sales conversation rather than as a novelty.

Powers

Identity Architecture — making sure the models know who you are before anything else is attempted.

We will run this on your brand and send you the results as a free AI Perception Report.


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