I scored 100 businesses on whether AI actually recommends them. Big brands are losing to indies.

A developer's audit of 100 businesses found that national brands score worst on AI recommendation readiness, averaging 75.5, while international companies lead with 91.5. The analysis, based on a controlled sample, shows that 79% of sites lack FAQ sections and 70% hide reviews, making it harder for AI models to cite them.

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.