Web3 marketing teams are trying to apply traditional SEO thinking to AI search and finding it does not work. The mechanics are different, the signals are different, and the content that earns rankings is not the same content that earns AI recommendations. This post maps out exactly what changes and what to do about it.
What LLM SEO is and how it differs from traditional SEO
Traditional SEO optimises pages to rank in Google results. LLM SEO optimises brands to appear in AI-generated answers. Traditional SEO is won through backlinks, keyword relevance, and technical crawlability. LLM SEO is won through entity clarity, content extractability, and consistent external brand presence. The tactics, metrics, and content formats are all different.
Traditional SEO gets you ranked. LLM SEO gets you recommended. These are different outcomes requiring different strategies.
For the complete LLM SEO framework for Web3, see Mastering AI Search for Crypto & Web3 Brands.
What stays the same between traditional SEO and LLM SEO
Technical crawlability, content quality, and external validation all matter in both traditional SEO and LLM SEO. The fundamentals of making your site readable, your content useful, and your brand credible translate directly. What changes is how these fundamentals are implemented and measured.
LLM SEO does not replace traditional SEO fundamentals — it extends them into a new context with different rules.
Shared fundamentals
- Technical accessibility — both Google and LLMs need to read your content
- Content quality — accurate, structured, useful content performs well in both
- External validation — third-party coverage builds authority for both
- Named authorship — credibility signals matter for both
What changes between traditional SEO and LLM SEO for Web3
The biggest changes are in content format, authority signals, and distribution channels. Backlinks lose primacy to brand mentions. Long-form articles lose primacy to extractable definition blocks. Google rankings lose primacy to share of voice in AI answers.
Everything that made you visible in Google still matters — but it is no longer sufficient for AI search visibility.
Side-by-side comparison
| Dimension | Traditional SEO | LLM SEO |
|—|—|—|
| Primary goal | Rank in Google | Appear in AI answers |
| Content format | Long-form keyword-rich articles | Short extractable definition blocks |
| Authority signal | Backlinks | Consistent brand mentions |
| Key platforms | Google, Bing | ChatGPT, Perplexity, Google AI |
| Distribution | Link building | Reddit, YouTube, Wikipedia |
| Measurement | Rankings, organic traffic | Share of voice in AI answers |
| Risk language | Often avoided | Required for AI trust |
| Entity definition | Nice to have | Non-negotiable |
Evidence
The Notabene case study shows how a Web3 compliance brand that was invisible in AI search despite solid Google rankings fixed LLM SEO separately from traditional SEO — and achieved a 39x increase in organic visitors alongside consistent AI recommendation.
Which to prioritise first for Web3 projects
For most Web3 projects, fix LLM SEO fundamentals first — specifically the technical and content layers — because these overlap heavily with traditional SEO and produce compound benefits. Then build the LLM-specific elements: entity definition, external mention strategy, and reinforcement on AI-trusted platforms.
For Web3 brands with limited resources, fixing LLM SEO foundations improves both AI visibility and Google performance simultaneously.
The LLM SEO for Web3 service and the crypto and blockchain SEO service are designed to work together for exactly this reason.
Conclusion
LLM SEO is not a replacement for traditional SEO. It is a parallel discipline that solves a different problem — being found and recommended by AI systems rather than ranked in search engines.
Web3 projects that build both will have visibility advantages in both discovery channels. Those that ignore LLM SEO will find an increasing share of their category’s discovery happening without them.
Download the free version of Mastering AI Search for Crypto & Web3 Brands: victoriaolsina.com/mastering-ai-search-for-web3/
If you want this implemented for your project, book a strategy call: calendly.com/victoria_olsina/45min
Frequently Asked Questions
Can a Web3 project do LLM SEO without traditional SEO?
Technically yes, but not advisably. Traditional SEO builds the crawlable, authoritative content foundation that LLM SEO depends on. A Web3 project with no traditional SEO foundation will struggle to build the technical and content layers LLM SEO requires. Traditional SEO and LLM SEO share enough fundamentals that building one without the other leaves value on the table.
Do backlinks help with LLM SEO?
Indirectly. Backlinks still contribute to domain authority and can influence which content gets crawled and learned by AI systems. But they are not the primary signal for AI recommendation — brand mentions across trusted platforms are. Backlinks help LLM SEO as a foundation, not as a primary strategy.
What content format works best for LLM SEO in Web3?
Short, self-contained explanation blocks: canonical definitions, bullet-point mechanics, FAQ responses, explicit risk statements, and criteria-based comparisons. These are structurally different from the long-form keyword-rich articles that perform well in traditional SEO. LLM SEO content is written to be extracted, not read linearly.
How do I measure LLM SEO performance for my crypto project?
Track share of voice in AI answers by running consistent prompts across ChatGPT, Perplexity, and Google AI Overviews monthly. Measure whether your brand is mentioned, whether it is cited as a source, and whether the description is accurate and confident. LLM SEO measurement is qualitative and prompt-based, not keyword-ranking based.
Is LLM SEO more important than traditional SEO for Web3 now?
For most Web3 projects in 2025 and beyond, LLM SEO is the higher-growth opportunity because it is underdeveloped — most competitors are not doing it. Traditional SEO in crypto is also competitive and slower to compound. LLM SEO offers Web3 projects a first-mover advantage that traditional SEO no longer provides.
