{"slug": "i-scored-100-businesses-on-whether-ai-actually-recommends-them-big-brands-are-to", "title": "I scored 100 businesses on whether AI actually recommends them. Big brands are losing to indies.", "summary": "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.", "body_md": "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?**\n\nI 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.)\n\nFull 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.\n\nCategory averages:\n\n| Category | Avg score |\n|---|---|\n| International | 91.5 |\n| B2B / niche SaaS | 81.1 |\n| Local | 79.8 |\nNational brands |\n75.5 (worst) |\n\nBig 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.\n\n| Problem | How many sites |\n|---|---|\n| No FAQ / no answer-ready sections | 79 |\n| Reviews/testimonials not visible as on-page text | 70 |\n| Pricing not visible | 49 |\n| Business not recommended for its own core prompt | 29 |\n| About / who-you-are unclear | 27 |\n| Weak or missing structured data | 9 |\n\nThe 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.\n\nThis 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.\n\nFull 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.", "url": "https://wpnews.pro/news/i-scored-100-businesses-on-whether-ai-actually-recommends-them-big-brands-are-to", "canonical_source": "https://dev.to/zeb_choudhry_eda2ce4ce1d3/i-scored-100-businesses-on-whether-ai-actually-recommends-them-big-brands-are-losing-to-indies-5ao8", "published_at": "2026-08-28 10:10:26+00:00", "updated_at": "2026-08-28 10:19:15.453764+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-products", "ai-tools"], "entities": ["GetVisus"], "alternates": {"html": "https://wpnews.pro/news/i-scored-100-businesses-on-whether-ai-actually-recommends-them-big-brands-are-to", "markdown": "https://wpnews.pro/news/i-scored-100-businesses-on-whether-ai-actually-recommends-them-big-brands-are-to.md", "text": "https://wpnews.pro/news/i-scored-100-businesses-on-whether-ai-actually-recommends-them-big-brands-are-to.txt", "jsonld": "https://wpnews.pro/news/i-scored-100-businesses-on-whether-ai-actually-recommends-them-big-brands-are-to.jsonld"}}