GEO for Crypto Brands: How to Get Cited by ChatGPT and Google AI
GEO for Crypto Brands: How to Get Cited by ChatGPT and Google AI
Written by
Hashcut Team
Key takeaways
AI answers are replacing clicks: Pew Research found Google users clicked a result in 8% of visits when an AI summary appeared, versus 15% without one.
Generative engine optimization (GEO) means making your project easy for AI systems to understand, trust and cite.
AI tools favour clear definitions, specific facts, consistent naming and sources they already trust.
Your own site, YouTube, credible media coverage and founder content all feed what AI says about you.
Test regularly: ask the main assistants about your project and your category, and track what they say.
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A growing share of research now happens inside AI assistants. Someone asks ChatGPT, Gemini, Perplexity or Google’s AI Overviews “what is the best DePIN network for compute” or “is this tokenization platform legit”, and gets an answer without visiting a single website.
That shift is measurable. A Pew Research Center study of real browsing data found that when Google showed an AI summary, users clicked a traditional result in 8% of visits, compared with 15% when no summary appeared. Pew also found longer, question-style searches were far more likely to trigger a summary.
For crypto brands, the question is no longer only “do we rank?” It is “what does AI say about us, and does it mention us at all?” That is generative engine optimization, or GEO.
How AI assistants decide what to say
AI systems build answers from sources they can access and consider reliable. In practice, they lean on content that is:
Clear: direct definitions and plain explanations they can quote
Specific: numbers, dates, names and concrete claims rather than adjectives
Consistent: the same name, description and facts across your site and the wider web
Corroborated: repeated by independent, credible sources, not only by you
A project described five different ways across its site, X bio, docs and press coverage gives AI systems nothing stable to repeat.
Step 1: Fix your one-line definition
Write one sentence that defines your project: what it is, who it is for and what it does. Use it, word for word, on your homepage, about page, docs, social bios and press materials. When an assistant is asked “what is [your project]”, this is the sentence you want it to return.
Step 2: Answer the questions your buyers ask
List the 20 to 30 questions people ask about your category and your project. Then publish clear answers on your own site:
“What is [category] and how does it work?”
“How is [project] different from [alternative]?”
“Is [project] safe? How is it audited?”
“How do I [core action] with [project]?”
Put the direct answer in the first two sentences, then expand. AI systems often lift that opening.
Step 3: Structure content so machines can read it
One clear H1 and logical H2 sections
Short paragraphs and descriptive headings phrased as questions people ask
Tables for comparisons and specifications
Schema markup for your organisation, articles and products
Dates on content, and regular updates to anything time-sensitive
Step 4: Earn mentions beyond your own site
AI assistants trust what others say about you more than what you say about yourself. Build that layer through:
Founder interviews on podcasts and video channels in your sector
Coverage in credible mainstream and industry media
Listings and data on the analytics platforms your category relies on
Talks and panels that get recorded and published
Video matters here too. YouTube transcripts and descriptions are text that AI systems can read. Our content repurposing guide shows how one interview becomes both.
Step 5: Test and track
Once a month, ask the major assistants a fixed set of questions about your project and your category. Record whether you are mentioned, how you are described, and which sources are cited. Fix gaps at the source: if an assistant gets a fact wrong, find where that version lives online and correct it.
Mistakes to avoid
Writing only for keywords. Stuffed pages read badly to people and machines alike.
Vague marketing language. “Revolutionary next-generation ecosystem” gives AI nothing to cite.
Inconsistent naming. Pick one spelling and one description, and use them everywhere.
Ignoring video. Unpublished interviews are invisible to AI.
Get found in AI answers
Hashcut builds the content that makes web3 brands easy to understand, for people and for AI: clear explainers, founder interviews, search-ready blogs and distribution across the channels AI systems read. Book a call to find out what AI says about your project today.
A growing share of research now happens inside AI assistants. Someone asks ChatGPT, Gemini, Perplexity or Google’s AI Overviews “what is the best DePIN network for compute” or “is this tokenization platform legit”, and gets an answer without visiting a single website.
That shift is measurable. A Pew Research Center study of real browsing data found that when Google showed an AI summary, users clicked a traditional result in 8% of visits, compared with 15% when no summary appeared. Pew also found longer, question-style searches were far more likely to trigger a summary.
For crypto brands, the question is no longer only “do we rank?” It is “what does AI say about us, and does it mention us at all?” That is generative engine optimization, or GEO.
How AI assistants decide what to say
AI systems build answers from sources they can access and consider reliable. In practice, they lean on content that is:
Clear: direct definitions and plain explanations they can quote
Specific: numbers, dates, names and concrete claims rather than adjectives
Consistent: the same name, description and facts across your site and the wider web
Corroborated: repeated by independent, credible sources, not only by you
A project described five different ways across its site, X bio, docs and press coverage gives AI systems nothing stable to repeat.
Step 1: Fix your one-line definition
Write one sentence that defines your project: what it is, who it is for and what it does. Use it, word for word, on your homepage, about page, docs, social bios and press materials. When an assistant is asked “what is [your project]”, this is the sentence you want it to return.
Step 2: Answer the questions your buyers ask
List the 20 to 30 questions people ask about your category and your project. Then publish clear answers on your own site:
“What is [category] and how does it work?”
“How is [project] different from [alternative]?”
“Is [project] safe? How is it audited?”
“How do I [core action] with [project]?”
Put the direct answer in the first two sentences, then expand. AI systems often lift that opening.
Step 3: Structure content so machines can read it
One clear H1 and logical H2 sections
Short paragraphs and descriptive headings phrased as questions people ask
Tables for comparisons and specifications
Schema markup for your organisation, articles and products
Dates on content, and regular updates to anything time-sensitive
Step 4: Earn mentions beyond your own site
AI assistants trust what others say about you more than what you say about yourself. Build that layer through:
Founder interviews on podcasts and video channels in your sector
Coverage in credible mainstream and industry media
Listings and data on the analytics platforms your category relies on
Talks and panels that get recorded and published
Video matters here too. YouTube transcripts and descriptions are text that AI systems can read. Our content repurposing guide shows how one interview becomes both.
Step 5: Test and track
Once a month, ask the major assistants a fixed set of questions about your project and your category. Record whether you are mentioned, how you are described, and which sources are cited. Fix gaps at the source: if an assistant gets a fact wrong, find where that version lives online and correct it.
Mistakes to avoid
Writing only for keywords. Stuffed pages read badly to people and machines alike.
Vague marketing language. “Revolutionary next-generation ecosystem” gives AI nothing to cite.
Inconsistent naming. Pick one spelling and one description, and use them everywhere.
Ignoring video. Unpublished interviews are invisible to AI.
Get found in AI answers
Hashcut builds the content that makes web3 brands easy to understand, for people and for AI: clear explainers, founder interviews, search-ready blogs and distribution across the channels AI systems read. Book a call to find out what AI says about your project today.
The world should see what you’re building.
Event coverage, founder interviews and video podcasts for web3 brands.
