In Web3, visibility is no longer just about headlines. It’s about what AI tells people when they ask about your project.
We help Web3 companies become the brand that AI recommends when users, investors, and developers ask about your category.
Trusted by global brands
THE Web3 Challenge
The Web3 PR playbook has changed. Most projects haven’t noticed.
Problem 01
Users Ask AI Before They Ask Crypto Twitter.
When a developer asks ChatGPT “what’s the best DeFi lending protocol” or an investor asks Perplexity “most promising Layer 2 blockchains,” they get a specific shortlist. Less than 15% of crypto projects have optimized for AI discoverability. If your project isn’t in the answer, you’re invisible to them.
Problem 02
Press Releases Don’t Build AI Authority.
The old Web3 PR playbook — mass press releases on newswire services doesn’t influence what AI recommends. AI models evaluate editorial credibility, not paid distribution. A single earned feature in a tier one mainstream or Web3 publication carries more AI recommendation weight than 50 syndicated press releases.
Problem 03
Your Competitors Are Engineering AI Visibility.
The best Web3 projects in 2026 are already optimizing for LLM visibility. They’re engineering how AI systems interpret and cite their clients’ projects. If your competitors are showing up in ChatGPT and Perplexity answers and you’re not, they’re capturing users, investors, and developer attention you’ll never see.
Problem 04
Your Technology Is Invisible to AI.
You’ve built a technically superior protocol, raised significant funding, and have strong on-chain metrics. But if that substance lives only in your documentation and community channels, without external validation, the model has no basis to recommend you over competitors with better authority signals.
Enter Authority GEO
In Web3, trust is the scarcest resource. AI evaluates trust through what it can verify.
Web3 is built on trustlessness at the protocol level, but brand trust still matters enormously at the adoption level. Users need to trust a project before they deposit assets. Investors need to trust a team before they commit capital. Developers need to trust an ecosystem before they build on it.
The discovery process for all three audiences is shifting to AI. When someone asks ChatGPT about the best wallets, protocols, or blockchain platforms, the model generates recommendations based on what it can verify through independent sources — editorial coverage, community discussion, developer documentation, and entity consistency across platforms.
We’ve worked in the blockchain and crypto space for over 8 years, securing 600+ media placements across the industry. We’ve seen firsthand how sustained earned media coverage compounds into lasting AI authority.
AI doesn't guess.
It verifies.
The authority signals AI checks before recommending a Web3 project.
Most Web3 companies have some of these. Almost none have all of them structured for AI extraction.
Editorial coverage in the publications your users trust.
Your project needs genuine editorial mentions in outlets AI trusts — CoinDesk, The Block, TechCrunch, Forbes, Decrypt, and respected niche publications. Sponsored placements and press release syndication don’t carry AI recommendation weight. Earned coverage does. Contextually matched placements — tied to your specific category and use case — drive recommendations far more effectively than generic crypto news.
Content structured for how AI processes SaaS queries.
GitHub repositories, developer docs, and technical documentation are massive authority signals for Web3 projects. ChatGPT heavily references GitHub documentation for technical queries. Well-structured README files, clear protocol descriptions, and comprehensive API documentation directly influence whether AI recommends your project for developer-focused queries.
Consistent entity signals across every platform.
AI cross-references your project across CoinGecko, CoinMarketCap, DeFi Llama, Crunchbase, GitHub, your website, and media mentions. If your CoinGecko description says one thing, your website says another, and your GitHub README tells a third story, AI loses confidence and defaults to a competitor with cleaner signals.
Review presence on the platforms that matter.
AI models heavily reference Reddit, Twitter/X, Discord (when indexed), GitHub, and crypto forums when evaluating project credibility. Domains with significant brand mentions on Reddit have roughly 4x higher chances of being cited by ChatGPT. For Web3, genuine community discussion is one of the strongest AI authority signals — far more powerful than manufactured hype.
How Web3 users Use AI
Four stages. If you’re missing from any of them, you lose.
| Stage | What the buyer asks AI | What AI needs from you |
|---|---|---|
| Discover | "What are the best projects for X?" | Presence in listicles, editorial coverage, and category content that establishes your firm as a known option |
| Compare | "Project A vs Project B for my use case" | Comparison content, differentiated positioning, and review presence that gives AI clear points of distinction |
| Validate | "Is Project A legit? Any red flags?" | Reviews, case studies, third-party mentions, and awards that AI can cite as independent proof |
| Choose | "Which Project is best for a usecase like mine?" | Use-case specific content, decision guides, and consistent entity signals that match the buyer's context |
OUR Financial Services APPROACH
The full GEO and PR program, built for Web3.
Organic PR
We secure editorial coverage and listicle inclusions in the publications AI trusts — CoinDesk, Cointelegraph, Investing.com, Forbes, Decrypt, and respected niche outlets. For Web3, earned editorial coverage is the highest-impact vector because AI cites editorial sources far more than syndicated press releases or paid placements.
Review Stimulation
We build your presence on the platforms AI references for Web3 evaluation — CoinGecko, CoinMarketCap, DeFi Llama, Dapp Radar, and project review platforms. We also engineer positive discussion signals on Reddit, Twitter/X, and relevant forums. For Web3, community sentiment is a critical AI authority signal that directly influences recommendations.
Specialized GEO Content
We create comparison guides, educational content, service explainers, and decision resources structured for AI extraction. When a consumer asks AI how your firm compares to alternatives, your content gives the model clear, authoritative information that positions your firm as the trusted option — without making claims that could raise compliance concerns.
Social Chatter
We build visibility on Crypto Twitter/X, Reddit (r/cryptocurrency, r/defi, r/ethereum, etc.), Discord, Telegram, and developer forums. AI models reference Reddit and Twitter discussions when evaluating project credibility — brands with significant Reddit mentions have roughly 4x higher citation chances on ChatGPT.
In-house Channel Optimization
We ensure your website, CoinGecko listing, CoinMarketCap profile, GitHub repositories, and all directory listings are consistent, structured, and machine-retrievable — from structured data to entity consistency across the entire Web3 ecosystem. The exact platforms are always based on what's needed for your project.
Targeted Paid Press Releases
We amplify key milestones — protocol launches, funding rounds, partnerships, mainnet upgrades, audit completions, TVL milestones — through premium distribution channels that AI models index. Web3 projects with a steady cadence of verifiable developments create fresh authority signals that compound over time.
How we work
From invisible to recommended – tailored to Web3 services.
Step 01
Discovery
We test your firm across hundreds of prompts Web3 users actually use. We map where your project appears, where competitors appear instead, and audit your review presence, editorial footprint, and entity consistency across all relevant platforms.
Step 02
Strategy
We build a prioritized roadmap. Whether the biggest gaps are social volume, missing from industry ranking, entity inconsistency, or missing educational content. The strategy is shaped by your specific market and regulatory environment.
Step 03
Execution
Simultaneous execution across all relevant vectors. PR campaigns targeting your industry’s key publications. In-house content optimized. New GEO content pieces published. Directories published. Entity signals aligned across platforms.
Step 04
Iteration
Continuous citation tracking across all major AI platforms. Monthly reports showing which prompts trigger your firm, which don’t, and what competitors are doing. Quarterly strategy reviews to adjust priorities based on what’s working and what isn’t.
Get Started
Find out if your brand is AI-ready.
Free Audit
Get a free AI visibility audit assessing your content, technical structures, and more. See exactly where you stand in under 48 hours.
No commitment. No retainer. Just data.
What it includes:
- AI citability & visibility score
- Technical foundations & data review
- Content & EEAT audit
- Optimization score for specific platforms
- Action Plan
How we think
Whether you’re a DeFi protocol or an enterprise blockchain, AI visibility follows the same rules.
We work with Web3 companies across the blockchain ecosystem. If your project depends on being discovered and trusted by users, investors, or developers, GEO applies to you. Here are some of the project types we’ve worked with:
- Layer 1 and Layer 2 blockchain protocols
- DeFi platforms and lending protocols
- Enterprise blockchain and B2B solutions
- NFT platforms and digital collectibles
- Web3 gaming and metaverse projects
- Crypto wallets and infrastructure providers
- DAOs and governance platforms
- Blockchain security and audit firms
The principle is the same regardless of category or stage: AI recommends the projects it can verify through independent sources. Your whitepaper is a claim. We build the verification layer.
Case Studies
Real results for real Web3 companies.
Case Study 02
Authority building that lasts years.
The context:
A DARPA-incubated startup competing against established players for government and enterprise contracts — in one of the noisiest industries on the internet.
The Outcome:
Years later, ChatGPT, Claude, Perplexity, and Gemini all recommend this company by name with high confidence — powered by the authority footprint we built.
Thanks to PolyGrowth, our local business is ranked #1 on Google for our most important keywords and has been recommended as the best option on ChatGPT for 2+ years now.
We really enjoyed working with the PolyGrowth team. The results were exactly as promised and we look forward to our next project with them.
"We highly recommend Simon and the PolyGrowth team. They were extremely easy to communicate with and provide an exceptional service with great turnaround time. We will continue to use their services long term and would encourage anyone else to do the same."
FAQs
Frequently asked questions about GEO for finance.
According to Intuit Credit Karma, 66% of Americans who use AI tools have used them for financial advice, rising to 82% among Gen Z and millennials. McKinsey reports nearly 40% of consumers in developed markets have used generative AI for financial purposes. Forrester predicts that by 2026, over half of under-50 consumers seeking financial advice will turn to AI tools like ChatGPT. Consumers use AI for everything from comparing savings rates and researching advisors to evaluating investment options and understanding mortgage terms.
Google Business reviews are the single most important signal for local financial services recommendations. Trustpilot and Better Business Bureau carry significant weight for trust-sensitive industries. NerdWallet, Bankrate, and SmartAsset are heavily cited by AI for product-specific queries. Industry-specific directories like NAPFA or FPA matter for advisory firms. Our audit identifies exactly which platforms AI references for your specific market segment.
AI models can’t evaluate credentials the way a human regulator or referral source would. They evaluate what they can find online: editorial coverage, reviews, directory listings, and entity consistency across platforms. A firm with excellent credentials but limited online third-party evidence is invisible to AI. The good news is that building this verification layer is straightforward for firms that already have the underlying quality — the gap is in digital visibility, not substance.
Yes — and often more effectively than in traditional marketing. AI models value specificity and verifiability over brand size. A boutique wealth management firm specializing in retirement planning for tech executives, with strong Google reviews and coverage in financial planning media, can outperform Goldman Sachs or Merrill Lynch for those specific queries. AI recommendations favor the most relevant, verifiable answer — not the biggest brand. Specialists win in AI.
We track citation frequency, recommendation positioning, and sentiment across all major AI platforms using prompt-by-prompt monitoring. Monthly reports include competitive benchmarking, trend analysis, and gap identification. We measure what matters: how often AI recommends the brand, in what context, and how that changes over time.
ChatGPT dominates consumer usage for financial queries, with Gemini growing rapidly. Google AI Overviews increasingly appear for financial product comparisons and “best of” searches. Perplexity is valuable for detailed comparison queries. Each platform cites different sources with limited overlap, which is why a multi-platform strategy is essential even for local financial services firms.
It depends on your starting point. Firms with existing editorial coverage and reviews can see initial citations within weeks on real-time platforms like Perplexity and ChatGPT. Firms building from zero need 2–3 months to establish the foundational authority layer. Becoming the go-to recommendation in a specific financial services niche typically takes 6–12 months of sustained effort. For firms in smaller or regional markets, results can come significantly faster.
Traditional financial marketing focuses on lead generation through advertising, content marketing, and referral programs. We focus on building the third-party authority layer that AI specifically evaluates: editorial coverage selected based on AI citation data, review presence across the platforms AI references, entity consistency across Google, industry directories, and regulatory databases, and content structured for AI extraction. Every placement serves a dual purpose: building reputation with human clients and building recommendation confidence with AI models. All content is developed with regulatory compliance in mind.