AI engines now decide which crypto projects get recommended. These guides explain how that works: starting from "what is AEO" and funneling down to the specifics that get your brand cited. Plain English, built for Web3 teams.
Read top to bottom, or jump to the one you need.
The plain-English definition. What Answer Engine Optimization is, why crypto buyers ask the AI before Google, how the prompt-to-recommendation pipeline works, and what the engines actually read. If you read one, read this.
Read the guide →Same goal, different game. Where the two overlap, where they diverge, and how to run both without doubling the work.
Read the guide →The exact signals that decide which projects ChatGPT, Perplexity, and Gemini cite (earned media, mentions, structure, entity footprint) and how to earn each one.
Read the guide →Once you've got the basics, these go from theory to your specific category.
The question we get asked most, answered with data. Why earned coverage beats your own blog for AI citations, why mentions matter more than backlinks, and why the outlet you pick decides whether any of it works.
Read the guide →Why a blast to 400 sites nobody trusts is not coverage, how citeOS scores 500+ crypto outlets on 5 signals, and how earned placements become citations across the AI engines buyers research with.
Read the guide →The highest-trust answer in crypto. The prompts, the sources, and the security signals that win deposits.
Read the guide →How protocols get cited. Where TVL, audits, and DefiLlama fit, and why engines play it safe.
Read the guide →How wallets win the safest-wallet answer. Security reputation and custody as the deciding signals.
Read the guide →Five criteria, ten points each, written down before any agency was scored. Every component score is printed, so if the weighting does not match how you buy, you can re-rank the table yourself.
Read the guide →ChatGPT reads other people’s pages about your category, not yours. Five steps that move a crypto brand from absent to named, each with a figure from our 39,948-citation study behind it, then our own 30-day log of running them.
Read the guide →A fixed prompt set, three states per answer, one log. What counts as movement, what is noise, and our own dated flips as the worked example.
Read the guide →Twenty prompts a first-time buyer actually types, five engines, 16 Sep 2026. Coinbase opens 46 of 100. Kraken takes fear and fees. Nine answers name nobody.
Read the guide →Five of the nine most-cited payment pages are written by payment companies. 59% of the volume.
Read the guide →39,948 citations tagged by hand in our April to August 2026 study. Reddit is 2.2%. Your own site caps near 8%. Listicles are the largest single format.
Read the guide →Six moves that get Perplexity to recommend you, ranked by what 1,000 measured AI answers actually cited.
Read the guide →ChatGPT's two-system model, and why to win Perplexity first and let presence compound into it.
Read the guide →1,000 observations across 10 exchanges. Every engine's top three is the same three names, and there are still three different winners.
Read the study →One says 62, one says 34, one says "highly visible." Where the divergence comes from, and the five disclosure questions that tell you which scores to trust.
Read the guide →Five categories of AEO tool, why the scores never agree, and the six questions that expose a dashboard pretending to be a measurement product. We build one, and we say so.
Read the guide →The one engine where your existing SEO work transfers directly, plus the crawler setting that quietly locks most crypto teams out of it.
Read the guide →Two disciplines share one name. The split, the evidence on what moves citations, and the three metrics worth reporting.
Read the guide →Four questions decide whether a GEO tool score can be acted on, and vendors talk about them least.
Read the guide →GEO gets nearly twice the searches of AEO and describes the same practice. The levers that actually move a generative answer.
Read the guide →Ninety-nine domains carry half of every AI citation in crypto. The full dataset, method and tables.
Read the study →The four capability layers these tools stack, the six questions to ask before signing, and when you do not need one at all.
Read the guide →Twenty brand-neutral questions, 100 answers, one day. Twenty-three different wallets took the first slot, and the leader took 18 of 100.
Read the comparison →Every tool gates engine access somewhere, and the gate usually sits one tier above where a buyer lands. Six read on the same day.
Read the comparison →Measuring where you stand is software. Changing where you stand happens on pages you do not own. What a real scope contains, and what it costs.
Read the comparison →Profound does not publish a rate. Seven alternatives on the four things you can check before a sales call: price, engines, prompt count, scoring weights.
Read the comparison →Four tiers named, zero figures shown. Six alternatives with published rates where they exist, plus Peec AI versus Profound answered directly.
Read the comparison →What AEO tools do for a crypto project, the four capabilities that make one crypto-native, and how five platforms compare.
Read the guide →Eight products scored on five published criteria, including our own with the conflict disclosed. It does not rank first.
Read the guide →Four buyer-shaped prompts across five engines. No tool, no budget, and the two-column read that tells you what to fix.
Read the guide →Where each term came from, the three places the difference genuinely matters, and the scope question worth more than the entire debate.
Read the guide →Each step builds on the last.
The fastest way to understand AEO is to run it on your own brand. Five engines, 100 observation points, about a minute. No card, no signup.
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