That rests on unique, people-first content, sound technical foundations and clear entity signals, because Google’s AI features sit on its core ranking and quality systems.
This guide takes a Web3 or FinTech site to a state where AI engines can find, quote and attribute it. Expect a few weeks of work at intermediate skill level. If you want the wider context first, read Victoria Olsina’s piece on Web3 brand visibility in AI search engines.
What you’ll need
Keep the toolkit small. Every item here maps to a step later on.
- Google Search Console verified for your domain, so you can see indexing and query data.
- A crawl tool such as Screaming Frog, to find blocked, broken or thin pages.
- Access to ChatGPT, Gemini and Perplexity, the engines Squarespace names alongside Google’s AI Overviews as AI-driven search surfaces.
- A CMS login with rights to edit pages, templates and structured data.
- A compliance contact who can sign off FinTech and crypto claims.
- Intermediate SEO skill: you should know what a canonical, a robots.txt rule and a status code are.
- A few weeks of calendar time, because indexing and AI answers update on their own schedule.
Takeaway: if you cannot get Search Console and CMS access this week, fix that before anything else.
Before you start
Two things break AI visibility before any clever tactic gets a chance: thin commodity pages and blocked crawling.
Google’s own guidance says AI features rely on its core Search ranking systems to retrieve pages through retrieval-augmented generation. If Googlebot cannot reach a page, no AI answer can ground itself on it.
FinTech and crypto pages carry a second risk. They are “your money or your life” topics, so every yield figure, fee claim and regulatory statement needs compliance sign-off before you rewrite anything. Settle that review loop now. Rewriting first and seeking approval later doubles the work.
Here is the failure-and-check map Victoria Olsina uses for the whole project.
| Step | What breaks if skipped | How to verify |
|---|---|---|
| Content | Pages restate what every exchange already says, so AI systems have no reason to pick yours | Each page answers a specific query with a view or data competitors lack |
| Technical access | Googlebot is blocked or pages fail, so they never enter the index AI answers draw from | URL Inspection shows indexed, HTTP 200, crawl allowed |
| Structure | Answers are buried in long paragraphs, so engines cannot lift a clean passage | Each H2 opens with a direct one or two sentence answer |
| Entity signals | AI answers describe your brand wrongly or confuse it with a similar token or protocol | Prompts about your brand return accurate descriptions |
| Citation checks | You keep ranking but never get cited or chosen inside an answer | A logged prompt set shows your URLs appearing as sources |
Takeaway: print this table and tick each row before you call the project done.
Step-by-step: how to do SEO for AI search
Search Engine Land puts the shift plainly: SEO is about ranking pages, while AI search is about being cited, trusted or chosen inside an answer. Ranking is the entry ticket. Citation is the prize.
Step 1: Audit crawl and index access
Crawl the site with your crawl tool and export every URL with its status code, indexability and robots directive.
Google states that pages must meet its technical requirements: Googlebot not blocked, an HTTP 200 response and indexable content. Meeting those covers AI formats too. Check your preview controls as well, because nosnippet, max-snippet and noindex limit how content appears in AI experiences.
Web3 sites fail here often. Docs live on a subdomain behind a JavaScript app, or a staging robots.txt ships to production.
Verify: URL Inspection in Search Console shows your top commercial and educational pages as indexed, with no unintended nosnippet tags.
Step 2: Rewrite pages as unique, non-commodity answers
List the pages that only summarise what is already published elsewhere. “What is a stablecoin” with no original angle is the classic offender.
Google says unique, compelling and useful content will likely influence your presence in generative AI search more than any other suggestion in its guide. It singles out a unique point of view, such as first-hand experience, over a summary of existing content.
For a UK FinTech, that means writing from your own product data, your FCA-facing compliance process or your own onboarding flow. For a DeFi protocol, it means explaining your mechanism, not the category.
Verify: for each rewritten page, name one fact or view a reader could not get from the top three results.
Step 3: Structure pages for extraction
Open every section with the answer, then the detail. Use question-shaped H2s that match how people actually prompt.
Google describes query fan-out: the model fires related sub-queries to gather more results. A page with clear sections can satisfy several of those sub-queries at once. Victoria Olsina’s guide to site structure for AI search shows how to group pages so that works across a whole site, and mapping pages to search intent across the Web3 marketing funnel decides which questions each page owns.
Verify: read only the first sentence under each H2. If it answers the heading on its own, the page is extractable.
Step 4: Build entity and brand signals
Make your brand unambiguous. Use one consistent name, one description and one set of facts across your site, docs, socials and listings.
Crypto brands suffer here because tickers, forks and similarly named protocols blur together. An LLM that cannot tell you apart from a rug-pulled namesake will hedge or skip you. Your X presence matters too, which Victoria Olsina covers in X SEO for AI search visibility.
Verify: ask each engine to describe your brand by name and confirm the description matches your own About page.
Step 5: Add structured data and page experience fixes
Add Organisation, Article and FAQ structured data where it genuinely describes the page. Google says structured data must match the visible content.
Then fix page experience. Google lists display across devices, latency and a clear split between main content and everything else. Wallet-connect pop-ups and cookie walls that hide the answer are common failures on Web3 sites.
Verify: Search Console’s rich result reports show no errors, and the main content is visible on a mobile screen without interaction.
Step 6: Test prompts across AI engines
Write a fixed set of prompts that your buyers would type: “best UK crypto custody for institutions”, “how do I pay contractors in USDC”. Run them in Google AI Mode, ChatGPT, Gemini and Perplexity.
Do not guess what the model searches behind the scenes. This method lets you see what ChatGPT searches when it answers, which tells you which sub-queries your pages must satisfy.
Verify: you have a spreadsheet with each prompt, engine, date, cited sources and whether your domain appears.
Step 7: Track citations and iterate
Rerun the same prompts on a fixed schedule. Compare cited sources over time and rewrite the pages that rank but never get quoted.
Automating the prompt runs saves hours, and Victoria Olsina covers that workflow in Web3 AI search with ChatGPT and automation. For a regulated example of the core work behind this, see the SEO for FinTech case study.
Setup takes an afternoon. Keeping citations takes discipline.
Verify: your citation log shows a trend line, not a single snapshot.
Troubleshooting
No citations at all
- Symptom: you rank on page one but never appear as an AI source.
- Cause: the content is commodity, so engines pick a page with a clearer or more original answer.
- Fix: repeat Step 2 and add first-hand data or a distinct view.
Wrong brand description in AI answers
- Symptom: ChatGPT or Gemini describes an old product or a different token.
- Cause: inconsistent entity signals across your site and profiles.
- Fix: align names and descriptions everywhere, then add Organisation structured data that matches the visible text.
Pages indexed but never quoted
- Symptom: URL Inspection shows indexed, yet the page never surfaces in answers.
- Cause: the answer is buried, or snippet controls restrict use.
- Fix: move the direct answer to the top of each section and remove unintended nosnippet or max-snippet limits.
Traffic drops while impressions hold
- Symptom: clicks fall on informational queries.
- Cause: AI answers satisfy the query on the results page.
- Fix: shift effort to queries with commercial intent and pages that earn the citation link. A Web3 SEO audit like the Bankless one shows how to find where the traffic went.
Conclusion
AI search does not replace SEO. It raises the bar on what earns a citation. Fix access, rewrite for originality, structure for extraction, clean up your entity and then measure citations, not just rankings.
Once the foundations hold, the right tooling speeds up tracking. Compare the options in Victoria Olsina’s guide to the best AI SEO platforms for Web3 and FinTech brands and pick one that logs citations across engines.
FAQ: Frequently Asked Questions
What is SEO for AI search?
Victoria Olsina defines SEO for AI search as applying core SEO so AI engines can retrieve, cite and trust your pages. It combines original content, clean technical access, extractable structure and consistent entity signals.
Is SEO still relevant for AI search?
Yes. Google states its generative AI features are rooted in its core ranking and quality systems, so standard SEO best practice still applies. Victoria Olsina treats strong classic SEO as the entry ticket to AI citations.
What are GEO, AEO and AIO?
They are alternative names for AI SEO. Squarespace lists GEO (Generative Engine Optimisation), AEO (Answer Engine Optimisation), AIO (AI Optimisation) and LLMO. All describe appearing in AI-driven results and answers.
Does Google need special markup for AI Overviews?
No special markup is required. Google says meeting its technical requirements covers AI formats.
How long does it take to see AI citations?
Recrawl speed, prompt competitiveness and the amount of content you rewrite all shape the timeline.
Which AI engines should Web3 brands test?
Test Google AI Overviews and AI Mode, ChatGPT, Gemini and Perplexity. Victoria Olsina recommends running the same buyer prompts in each, because AI engines can return different sources for similar searches.
Get your brand cited in AI search
Victoria Olsina’s AI SEO and GEO service helps crypto, fintech and AI brands get ranked on Google and cited by ChatGPT, Perplexity and Google AI Overviews. Book a free strategy session to see where your brand stands in AI search today.
