# I scored 100 businesses on whether AI actually recommends them. Big brands are losing to indies. > Source: > Published: 2026-08-28 10:10:26+00:00 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](https://getvisus.com)). But this post is the data and the takeaways, not a pitch — you can act on every finding here without any tool. 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. | 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 | 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. 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](https://getvisus.com/ai-visibility-benchmark-2026). Happy to answer methodology questions in the comments.