How to fix token page schema errors that block AI citations

Error 1: Using Product or Article schema instead of FinancialProduct

The single most common error on token pages: using Product schema. Tokens are not consumer products. They're financial instruments. The right type is FinancialProduct, with a category property to disambiguate the specific token type (utility token, governance token, stablecoin, etc).

Why this matters: when an AI engine sees Product schema with a token name, it categorizes the page alongside e-commerce items. The page then gets ranked against unrelated products on price, ratings, and shipping data. None of those signals exist on a token page. The AI engine downweights the page because the signals it expects are missing.

The fix: Replace "@type": "Product" with "@type": "FinancialProduct". Add "category": "Cryptocurrency" or a more specific value. For tokens with a clear function classification (stablecoin, governance, utility), use the specific category in your description and the additionalType property pointing to a Wikidata or schema extension URL.

Error 2: Missing tickerSymbol property

Token pages without a tickerSymbol property lose disambiguation power. Two tokens can share a name (USD vs USDC, BNB the coin vs Binance the company). Without the ticker, the AI engine guesses based on context, and guesses wrong about a third of the time per our test set.

The fix: Add "tickerSymbol": "YOUR_TICKER" at the top level of your FinancialProduct schema. For tokens on multiple chains with the same ticker, also add "identifier" properties that include the chain ID plus contract address. This is how Coinbase, Etherscan, and CoinGecko schemas distinguish wrapped versions of the same asset.

Example: "tickerSymbol": "USDC", "identifier": [{"@type": "PropertyValue", "propertyID": "contract-eth", "value": "0xA0b86..."}].

Error 3: No blockchain or contract address declaration

The schema needs to tell the AI engine which chain the token lives on. The schema.org vocabulary doesn't have a dedicated blockchain property, so use additionalProperty with a clear name.

The fix:

"additionalProperty": [
  {"@type": "PropertyValue", "name": "Blockchain", "value": "Ethereum"},
  {"@type": "PropertyValue", "name": "Contract Address", "value": "0xA0b86..."},
  {"@type": "PropertyValue", "name": "Token Standard", "value": "ERC-20"}
]

This block is the most-cited element of token schema in Perplexity's responses about specific tokens. The AI engine reads these properties and includes them verbatim in answers like 'is <TOKEN> on Ethereum or Solana.'

Error 4: Generic boilerplate description

The schema description field is what AI engines often quote directly. If your description says 'A revolutionary blockchain project bringing innovation to DeFi,' you get the citation rate you deserve, which is zero.

The fix: Write a description that answers three questions in 25 words or less: (1) what the token does, (2) what makes it different, (3) one concrete metric. Example: 'EIGEN is EigenLayer's restaking governance token. It controls slashing parameters for $14B+ restaked ETH across 16 AVS protocols.'

That description is specific, contains a verifiable number, and names a defining concept. Compare to: 'EIGEN is the governance token of EigenLayer, the leading restaking protocol.' Same length, no useful information. AI engines pick the first version 4 times out of 5 in our citation tests.

Error 5: Broken or missing sameAs links

The sameAs array is your entity disambiguation. It tells the AI engine 'this token, on my page, is the same entity as the one on CoinGecko, CoinMarketCap, and Etherscan.' Without it, the engine guesses based on token name alone, and conflates similar-named tokens.

The fix: Include at minimum your CoinGecko page, CoinMarketCap page, and primary block explorer link. Verify each URL returns 200. Broken sameAs links signal stale or auto-generated schema, which AI engines weight down.

"sameAs": [
  "https://www.coingecko.com/en/coins/your-token",
  "https://coinmarketcap.com/currencies/your-token/",
  "https://etherscan.io/token/0xA0b86..."
]

Error 6: Inflated or fake aggregateRating

We see token pages claiming aggregateRating with 5 stars from 12,000 reviews. There is no public review platform for tokens with 12,000 reviews. Google catches this. AI engines catch it harder.

The fix: Remove fabricated ratings. If you genuinely have ratings from a legitimate source (Trustpilot for your exchange, App Store reviews for your wallet), use the real numbers and reference the source via ratingProvider. If you don't have legitimate ratings, omit the property entirely.

The penalty for fake ratings isn't a manual review. It's worse. AI engines start treating your entire schema as untrustworthy, which downweights your citation rate across the board.

Error 7: Tangled @graph with conflicting types

Some token pages ship 4 to 6 schema blocks, each claiming to be the primary entity. Browser dev tools show overlapping @id values, conflicting types, and circular references. The AI engine picks one at random or skips them all.

The fix: Use one @graph wrapper with clearly distinct @id values. Each node has a unique @id with a URL anchor (#token, #breadcrumb, #faq). Reference between nodes by @id, not by duplicating data.

Validate the final structure in the schema.org validator. If it reports multiple primary entities, simplify. One token page should have exactly one primary FinancialProduct node.

Common questions