102 brand diagnostics. Real scores. The results challenge everything brands assume about AI search performance.
The Data
We've run 102 brand diagnostics through Anchor. 88 are complete. The results are not what we expected.
The brands winning in AI search aren't the ones with the biggest budgets or the most brand recognition. They're the ones with the deepest community footprint — discussion threads, structured Q&A, comparison content written by real users.
Here's what we found.
The Full Leaderboard
| Brand | Category | AI Visibility Score | Tier |
|---|---|---|---|
| 小红书 (XiaoHongShu) | Social / Community | 89/100 | Excellent |
| Solana | Crypto / Blockchain | 83/100 | Excellent |
| Notion | Productivity / SaaS | 73/100 | Good |
| 完美日记 (Perfect Diary) | Beauty / Consumer | 71/100 | Good |
| OpenAI | AI / Technology | 71/100 | Good |
| Ethereum | Crypto / Blockchain | 67/100 | Good |
| 伊藤園 (Itoen) | Beverage / FMCG | 62/100 | Fair |
| Nike | Apparel / Legacy | 58/100 | Fair |
Score formula: Discovery × 60% + Brand Representation × 40%. Discovery measures whether AI models surface the brand unprompted. Brand Representation measures the accuracy and depth of how the brand is described.
Finding #1: Community-Driven Brands Beat Legacy Giants
小红书 scored 89/100. Nike scored 58/100.
Nike has 50+ years of brand equity, billions in annual revenue, and more ad spend than most countries' GDP. XiaoHongShu is a Chinese social commerce platform that most Western users have never heard of. And yet in AI visibility, it beats Nike by 31 points.
Why? Because 小红书 is discussed, not just known. The platform generates millions of user-written reviews, tutorials, and comparisons — exactly the type of content AI models learn to cite. When someone asks an AI "what app do Chinese Gen Z users use for product discovery?", the answer is XiaoHongShu, backed by thousands of structured community posts.
Nike gets mentioned. XiaoHongShu gets recommended. That's the gap.
Finding #2: Crypto Has Outsized AI Visibility
Solana scored 83/100. Ethereum scored 67/100. Both outperform Nike and OpenAI — two of the most famous brands on earth.
Crypto communities are AI visibility machines. Reddit's r/CryptoCurrency, r/solana, and r/ethereum contain millions of posts where users ask specific questions ("which blockchain is faster?", "Solana vs Ethereum gas fees?") and get detailed, structured answers. That's the exact format AI models are trained to extract and cite.
The lesson isn't "become a crypto brand." It's that structured Q&A content, written at scale by engaged communities, is worth more than any press release.
Finding #3: 64% of Brands Are Invisible to AI
This is the number that should concern you most.
Across our 88 completed diagnostics, 64% of brands score below 60/100. That means most brands — including well-funded, actively-marketed ones — are effectively invisible when AI models answer questions about their category.
A score below 60 means AI models either don't surface the brand unprompted, or they describe it with significant gaps and inaccuracies. In practice, this means when a potential customer asks ChatGPT for a recommendation, your brand isn't in the answer.
Not "ranked lower." Not "ranked on page two." Not in the answer at all.
Finding #4: Discovery Rate Is the Deciding Variable
Our score formula weights Discovery at 60% and Brand Representation at 40%. This weighting reflects what we've observed in the data: brands with high discovery scores consistently outperform brands that are well-described but rarely surfaced.
You can have a perfect brand description — accurate, detailed, well-sourced — and still score below 60 if AI models don't discover your brand in response to category-level queries.
The brands that score highest (89, 83, 73) all share one trait: they appear organically across a wide range of query types, not just brand-name searches. They're mentioned when someone asks about "social shopping apps," "fast blockchains," and "note-taking tools" — without their brand name ever appearing in the question.
That's real AI visibility. And it can't be bought with ad spend.
What Separates High-Scorers From the Rest
Across our dataset, three content patterns consistently predict high AI visibility scores:
1. Reddit and forum presence at scale
Not brand-controlled. Not press releases. Real users discussing the brand in response to real questions. r/Notion has 350,000+ members asking and answering Notion-specific questions. That corpus is enormously valuable for AI training and citation.
2. Comparison content
Articles titled "Solana vs Ethereum: which is faster in 2025?" are AI gold. They answer the exact structured questions AI models are asked. Brands that generate (or inspire) comparison content score significantly higher than brands that don't.
3. Structured Q&A
FAQ pages, Stack Overflow answers, Quora threads, support documentation — any content that pairs a specific question with a specific answer trains AI models to cite the brand in relevant contexts. XiaoHongShu's own platform is essentially a structured Q&A engine for consumer products.
Key takeaway
AI models cite content that explains and compares, not content that just mentions. Volume of mentions is far less important than the depth and specificity of discussion.
FAQ: AI Brand Visibility
Q: What is an AI visibility score and how is it calculated?
An AI visibility score measures how well a brand is discovered and represented by AI language models like ChatGPT, Claude, and Gemini. Anchor's score is calculated as Discovery (60%) × Brand Representation (40%), where Discovery measures unprompted appearance in AI responses and Brand Representation measures the accuracy and depth of how the brand is described.
Q: What's considered a good AI visibility score?
In our dataset of 88 completed diagnostics, scores of 70+ are considered Good, 80+ are Excellent. The median score is below 60. 64% of brands score under 60/100, meaning most brands have significant AI visibility gaps.
Q: Why do community-driven brands score higher on AI visibility?
AI models are trained on and cite content that answers specific questions with structured information. Community platforms (Reddit, forums, review sites) generate millions of such Q&A documents. Brands with large, active communities produce vastly more of this citable content than brands that rely on controlled marketing channels.
Q: Why does crypto rank so high in AI visibility?
Crypto communities are prolific generators of structured comparison content. Questions like "Solana vs Ethereum for NFTs" generate thousands of detailed responses across Reddit, Stack Exchange, and developer forums — exactly the format AI models learn to extract and cite. Solana's 83/100 score reflects this community depth.
Q: How can a brand improve its AI visibility score?
Three levers with the highest measured impact: (1) Build Reddit/forum presence where real users discuss your brand in response to questions, (2) Create or inspire comparison content that names your brand alongside competitors in specific use-case contexts, (3) Publish structured FAQ and Q&A content that matches the exact questions AI models are asked about your category.