Classic SEO measures whether you rank on Google. But AI answers are quietly eating the ten blue links, and that raises a different question with different signals: when someone asks ChatGPT, Claude or Google AI for a recommendation, can the model actually understand, trust and cite your business?
I wanted real data instead of vibes, so I ran a controlled audit of 100 businesses — 25 local, 25 national, 25 international, 25 niche B2B/SaaS — scoring how well each site gives AI systems what they need to recommend it. (Audit date: 2026-05-31.)
Full disclosure up front: I build a tool that does this scoring (GetVisus). But this post is the data and the takeaways, not a pitch — you can act on every finding here without any tool.
The surprising part: brand size didn't save anyone
- Bold Street Coffee, Mowgli, a local charity → 100/100
- Pret A Manger → 32. Greggs → 52. giffgaff → 53. Smarty → 29
- A well-known local venue → 14/100
Category averages:
| Category | Avg score |
|---|---|
| International | 91.5 |
| B2B / niche SaaS | 81.1 |
| Local | 79.8 |
| National brands | 75.5 (worst) |
Big national brands often have beautiful, JS-heavy sites that are hard for an LLM to extract facts from — while a tiny coffee shop with a clear, text-first page wins outright.
The most common problems (out of 100)
| Problem | How many sites |
|---|---|
| No FAQ / no answer-ready sections | 79 |
| Reviews/testimonials not visible as on-page text | 70 |
| Pricing not visible | 49 |
| Business not recommended for its own core prompt | 29 |
| About / who-you-are unclear | 27 |
| Weak or missing structured data | 9 |
What actually moves the needle (all free to do)
- Put a real FAQ / Q&A block on key pages, phrased the way customers actually ask. Answer-ready text is the single biggest gap.
- Show reviews and testimonials as text on the page — not just a Trustpilot logo an LLM can't read.
- Make pricing, or at least a price range/scope, visible. "Contact us" tells an AI nothing.
- Make the entity obvious: who you are, what you sell, who it's for, where you operate — in plain text near the top.
- Add basic schema (Organization, LocalBusiness, FAQ) — but only for facts that are visible on the page.
The pattern across every 100/100 site was identical: the business entity, the offer, the proof, and the "who it's for" boundaries were all trivially easy to extract. The low scorers made the AI guess — and models don't guess in your favour.
The honest caveat
This is a directional benchmark on a controlled sample, not a market-wide study, and not proof of exact revenue causation. The scoring reflects a model of what LLMs reward, not ground-truth from the model providers. But as AI answers replace the classic search results, "can an LLM cite you?" is becoming a real commercial question — and most sites, including big ones, are quietly failing it.
Full methodology and the 100-row dataset are in the benchmark report. Happy to answer methodology questions in the comments.
