How visible are the world's top crypto exchanges, blockchain protocols and Web3 projects to AI search engines? See who ChatGPT, Perplexity and Gemini are actually citing.
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Full Crypto & Web3 Leaderboard →Crypto buyers rely heavily on AI assistants for due diligence. If your project isn't cited by ChatGPT or Perplexity when someone asks "is X legit?", you're invisible at the most critical point in the funnel.
We audit eight categories: EEAT content, AI citability, AI platform readiness, structured data, technical SEO, brand authority, topical authority and platform optimisation. Each is weighted and combined into a score out of 100.
The average Crypto and Web3 score is just 36/100 - the lowest of any sector we track. Not one crypto brand has reached AI-Ready tier. This is a massive opportunity for projects that move first.
The crypto industry thrives on attention and trust, both of which are increasingly mediated by AI assistants. When someone asks which decentralised exchange has the lowest fees, or which layer-2 network is best for DeFi, the AI response shapes their next action. Projects that fail to appear in those answers lose users to competitors who have invested in being discoverable.
(How AI search visibility works)Web3 audiences are early adopters who disproportionately use AI tools for research. This makes AI visibility especially impactful in crypto: your target users are the ones most likely to bypass traditional search and go straight to an AI assistant for recommendations.
Trust is paramount in an industry plagued by scams. When AI systems consistently cite your project as a legitimate, well-documented protocol, it carries a trust signal that no amount of paid promotion can replicate.
Crypto documentation often lives in GitHub repositories, Discord servers and Notion workspaces. While these platforms serve the community well, they are not consistently indexed by AI crawlers. The result is a significant gap between what the community knows about a project and what AI systems can discover.
Technical complexity creates another barrier. Blockchain protocols involve concepts that are difficult to explain concisely, and many projects default to jargon-heavy whitepapers rather than the plain-language summaries AI assistants need to generate accessible answers.
The fast pace of the industry means content becomes outdated rapidly. Tokenomics change, new chains launch and protocol upgrades render old documentation inaccurate. AI systems that encounter contradictory or outdated information may simply exclude a project from recommendations rather than risk providing incorrect details.
Crypto projects should bridge the gap between community documentation and structured, publicly accessible web content that AI systems can parse and cite with confidence.
Move key documentation out of GitHub wikis and Notion into a proper documentation site with clean URLs, proper heading structure and search-friendly architecture. Include plain-language explainers alongside technical specifications.
Maintain a dedicated page with up-to-date token distribution, total supply, circulating supply and utility information. Mark this content with clear dates so AI systems can assess freshness and accuracy.
Create content that honestly compares your protocol to alternatives, covering strengths and trade-offs. AI assistants frequently generate comparison responses, and having your own well-structured comparison increases accuracy and visibility.
For established projects, a well-sourced Wikipedia article and comprehensive Wikidata entry provide authoritative signals that AI systems rely on heavily. These entries serve as trust anchors in AI-generated responses.
Publish beginner-friendly guides that explain what your protocol does in simple terms. This content captures the large volume of queries from users who are new to crypto and asking AI assistants for plain-language explanations.
Social media presence contributes to brand awareness but has limited direct impact on AI visibility. AI assistants primarily cite structured web content, documentation and authoritative references. A strong social presence is valuable, but it needs to be supported by well-structured website content for AI systems to reference reliably.
Focus on publishing clear descriptions of supported assets, fee structures, security audits and smart contract addresses on your public website. Ensure your documentation includes plain-language summaries of how each feature works, and keep all numerical data current. AI systems prefer citing sources that are comprehensive, accurate and easy to parse.
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