Deployable JSON-LD blocks for AI citation.

Pre-written schema blocks for the page types AI engines actually cite. Drop into a <script type="application/ld+json"> tag in your page head, fill in the bracketed values, validate at validator.schema.org. Annotated with notes on what each property does and which AI engines read which properties.

How to use these blocks

1. Copy the block for the page type you are building.
2. Replace every bracketed placeholder (e.g., [YOUR FIRM NAME]) with the actual value for your firm.
3. Paste inside <script type="application/ld+json">...</script> in the page head.
4. Validate at validator.schema.org. The validator should report no warnings.
5. Test the page renders correctly. Schema is invisible to humans but should not break the page.
6. Wait for AI engines to re-index (typically 4-8 weeks. See your monthly NeverRanked measurement for confirmation).

One page can have multiple schema blocks. A service-specific landing page might have Service + LocalBusiness + FAQPage + BreadcrumbList all on the same page. This is normal and AI engines handle it correctly.

LocalBusiness

The root schema for any local-service firm (CPA, attorney, dentist, wealth manager, bank branch, med spa, restaurant). Tells AI engines the firm exists, where it is, what it does, and how to reach it. Deploy this on the homepage and any location-specific page.

The block

// Drop inside <script type="application/ld+json">...</script>
{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "@id": "https://[YOUR DOMAIN]/#localbusiness",
  "name": "[YOUR FIRM NAME]",
  "url": "https://[YOUR DOMAIN]/",
  "telephone": "+1-[AREA CODE]-[NUMBER]",
  "email": "[CONTACT EMAIL]",
  "image": "https://[YOUR DOMAIN]/[PATH TO PHOTO].jpg",
  "priceRange": "$$",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "[STREET ADDRESS]",
    "addressLocality": "[CITY]",
    "addressRegion": "[STATE 2-LETTER]",
    "postalCode": "[ZIP]",
    "addressCountry": "US"
  },
  "geo": {
    "@type": "GeoCoordinates",
    "latitude": "[LAT]",
    "longitude": "[LNG]"
  },
  "openingHoursSpecification": [{
    "@type": "OpeningHoursSpecification",
    "dayOfWeek": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"],
    "opens": "08:00",
    "closes": "17:00"
  }],
  "sameAs": [
    "https://www.linkedin.com/company/[YOUR LINKEDIN]",
    "https://www.facebook.com/[YOUR FACEBOOK]",
    "https://[OTHER PROFILE]"
  ]
}

Property notes

Service

One block per distinct service the firm offers. Deploy on service-specific landing pages. The most important schema for long-tail-by-service queries (e.g., "fee-only tax advisor", "estate planning attorney").

The block

{
  "@context": "https://schema.org",
  "@type": "Service",
  "serviceType": "[EXACT SERVICE NAME]",
  "name": "[SERVICE NAME AS A BUYER WOULD SAY IT]",
  "description": "[ONE PARAGRAPH DESCRIBING WHAT THE SERVICE COVERS, WHO IT'S FOR, AND WHAT THE DELIVERABLE IS. 50-150 WORDS.]",
  "provider": {
    "@id": "https://[YOUR DOMAIN]/#localbusiness"
  },
  "areaServed": {
    "@type": "AdministrativeArea",
    "name": "[CITY OR REGION YOU SERVE]"
  },
  "audience": {
    "@type": "Audience",
    "audienceType": "[BUYER TYPE: small business, individuals, nonprofits, etc.]"
  },
  "offers": {
    "@type": "Offer",
    "priceCurrency": "USD",
    "price": "[PRICE OR PRICE RANGE]",
    "priceSpecification": {
      "@type": "PriceSpecification",
      "priceCurrency": "USD",
      "price": "[PRICE]",
      "description": "[Hourly, project-based, retainer, etc.]"
    }
  }
}

Property notes

FAQPage

One of the highest-leverage schemas for AEO. AI engines preferentially cite pages with FAQPage schema for question-shaped queries because the structured Q&A maps cleanly to what a buyer is asking. Deploy on service pages, location pages, and any page where buyers commonly have follow-up questions.

The block

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "[A QUESTION YOUR BUYER ACTUALLY ASKS]",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "[DIRECT, COMPLETE ANSWER. 2-5 SENTENCES. WRITE AS IF QUOTED BY AI.]"
      }
    },
    {
      "@type": "Question",
      "name": "[ANOTHER REAL QUESTION]",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "[DIRECT ANSWER]"
      }
    }
  ]
}

Rules for the FAQ

• Questions must be real. Use questions buyers actually ask, not marketing-shaped questions. AI engines preferentially cite pages where the Q&A maps to common buyer intent.
• Answers must be direct. 2-5 sentences. AI engines quote the text field verbatim. Write it as if it's about to be the AI's answer to a buyer.
• Visible AND schema. The same Q&A must appear in visible body text on the page, not just in schema. AI engines cross-check.
• 5-8 questions is the sweet spot. Fewer than 3 looks thin. More than 12 dilutes signal.
• No nested HTML in answers. Plain text only. <br> or markup breaks AI quoting.

Person

Named partners, attorneys, advisors, principals. Critical for high-trust professional-services categories (law, wealth, accounting) where AI engines cite specific named professionals more often than firms.

The block

{
  "@context": "https://schema.org",
  "@type": "Person",
  "@id": "https://[YOUR DOMAIN]/team/[SLUG]#person",
  "name": "[FULL NAME]",
  "jobTitle": "[ROLE: Partner, Senior Wealth Advisor, etc.]",
  "image": "https://[YOUR DOMAIN]/[PHOTO PATH].jpg",
  "description": "[ONE-PARAGRAPH BIO. 50-100 WORDS. NAME THE PERSON'S SPECIALTY, NOT GENERIC PRAISE.]",
  "worksFor": {
    "@id": "https://[YOUR DOMAIN]/#localbusiness"
  },
  "alumniOf": {
    "@type": "EducationalOrganization",
    "name": "[INSTITUTION]"
  },
  "hasCredential": [
    "[CREDENTIAL: CPA, JD, CFP, MD, etc.]",
    "[ADDITIONAL CREDENTIAL]"
  ],
  "knowsAbout": [
    "[SUBJECT AREA THIS PERSON SPECIALIZES IN]",
    "[ANOTHER SUBJECT AREA]"
  ],
  "sameAs": [
    "https://www.linkedin.com/in/[LINKEDIN SLUG]",
    "https://[OTHER PROFESSIONAL PROFILE]"
  ]
}

Property notes

Article

For case studies, named-byline thought leadership, technical explainers. Critical for high-trust professional services where editorial presence drives training-data engine citations over time.

The block

{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "[ARTICLE TITLE, <= 110 CHARS]",
  "description": "[ONE-SENTENCE SUMMARY]",
  "image": "https://[YOUR DOMAIN]/[HERO IMAGE].jpg",
  "datePublished": "YYYY-MM-DD",
  "dateModified": "YYYY-MM-DD",
  "author": {
    "@id": "https://[YOUR DOMAIN]/team/[AUTHOR SLUG]#person"
  },
  "publisher": {
    "@id": "https://[YOUR DOMAIN]/#localbusiness"
  },
  "mainEntityOfPage": {
    "@type": "WebPage",
    "@id": "https://[YOUR DOMAIN]/[ARTICLE PATH]"
  },
  "about": [
    "[SUBJECT AREA]",
    "[ANOTHER SUBJECT AREA]"
  ]
}

Rules for Article

• Always reference a Person via author.@id. Anonymous Articles get cited less. AI engines preferentially cite named-byline content.
• datePublished and dateModified matter. AI engines deprioritize stale content. Updated dates keep articles citation-eligible longer.
• about is the most overlooked property. Specific subject areas help AI route the article to the right query intents.

Offer

For service pages with transparent pricing. AI engines cite price-transparent pages more often for budget-shaped queries (e.g., "affordable", "best value", "under $X").

The block

{
  "@context": "https://schema.org",
  "@type": "Offer",
  "name": "[OFFER NAME]",
  "description": "[WHAT THE OFFER INCLUDES]",
  "price": "[PRICE NUMBER, NO CURRENCY SYMBOL]",
  "priceCurrency": "USD",
  "availability": "https://schema.org/InStock",
  "validFrom": "YYYY-MM-DD",
  "itemOffered": {
    "@type": "Service",
    "name": "[SERVICE NAME]"
  },
  "priceSpecification": {
    "@type": "UnitPriceSpecification",
    "price": "[PRICE]",
    "priceCurrency": "USD",
    "unitText": "[per hour, per project, per month, etc.]"
  }
}

For ranges, use PriceRange instead of Offer. For free initial consultations, set price to "0" with description noting "initial consultation."

BreadcrumbList

Site navigation context. Tells AI engines how this page fits in your site structure. Particularly important for service-specific or location-specific deep pages.

The block

{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    {
      "@type": "ListItem",
      "position": 1,
      "name": "Home",
      "item": "https://[YOUR DOMAIN]/"
    },
    {
      "@type": "ListItem",
      "position": 2,
      "name": "Services",
      "item": "https://[YOUR DOMAIN]/services/"
    },
    {
      "@type": "ListItem",
      "position": 3,
      "name": "[SPECIFIC SERVICE]",
      "item": "https://[YOUR DOMAIN]/services/[SLUG]"
    }
  ]
}

AggregateRating

For pages displaying review summaries. Use only with real, verifiable reviews. Fake or unverified ratings will get the page penalized.

The block

{
  "@context": "https://schema.org",
  "@type": "AggregateRating",
  "itemReviewed": {
    "@id": "https://[YOUR DOMAIN]/#localbusiness"
  },
  "ratingValue": "[ACTUAL AVERAGE, e.g., 4.8]",
  "bestRating": "5",
  "worstRating": "1",
  "reviewCount": "[ACTUAL COUNT]"
}

Important: ratingValue and reviewCount must reflect a verifiable source (Google Business Profile, Yelp, etc.). Inflated or fabricated values violate Google's structured-data guidelines and risk de-indexing.

Organization

The umbrella schema for the firm as an entity (separate from a specific LocalBusiness location). Use for multi-location firms or firms whose primary entity is more abstract than a single physical location.

The block

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://[YOUR DOMAIN]/#organization",
  "name": "[FIRM NAME]",
  "url": "https://[YOUR DOMAIN]/",
  "logo": "https://[YOUR DOMAIN]/[LOGO PATH]",
  "description": "[ONE-PARAGRAPH FIRM DESCRIPTION]",
  "foundingDate": "YYYY",
  "founders": [{
    "@type": "Person",
    "name": "[FOUNDER NAME]"
  }],
  "areaServed": {
    "@type": "AdministrativeArea",
    "name": "[REGION YOU SERVE]"
  },
  "sameAs": [
    "https://www.linkedin.com/company/[SLUG]",
    "https://en.wikipedia.org/wiki/[WIKI SLUG IF EXISTS]"
  ]
}

Common mistakes to avoid

• Schema that contradicts visible page content. AI engines cross-check. If schema says you serve Hawaii and the body text says California, both signals get downweighted.
• Generic description fields. "Leading provider of services in our category" tells AI nothing. Specific, deliverable-focused descriptions get quoted.
• Schema-only with no visible counterpart. The FAQ, the service description, the address all need to appear in body text too. Schema-only signals get treated as cloaking.
• Stale dateModified. Update when you make material changes. AI engines penalize content marked fresh that hasn't actually changed.
• Missing @id linkages. Without @id, AI engines can't connect Service to LocalBusiness to Person on the same page. Add stable @id values everywhere.
• One giant block for everything. Use separate <script type="application/ld+json"> tags per schema type. Easier to validate, easier to update.

Validation

After deploying any schema:

1. Paste your live URL into validator.schema.org.
2. Fix any errors (these block AI engines from reading the schema at all).
3. Address warnings where they apply (these reduce AI confidence in the schema).
4. For Google-specific validation, also test at Google Rich Results Test.
5. Re-validate any time you change the schema.

What happens next

Schema deployment is necessary but not sufficient for AI citation. The full path:

1. Deploy the schema matching the page's intent (this library).
2. Match the body content shape the cited competitors use (median word count, H2 structure, FAQ presence, all surfaced in your per-query NeverRanked playbook).
3. Internal link the page from existing high-traffic site sections so crawlers find it within the first re-index cycle.
4. Wait 4-8 weeks for AI engines to re-index. Training-data engines (Claude, Gemma) take much longer. They reflect schema changes on the next model training cycle.
5. Verify in your monthly NeverRanked measurement that the page is now being cited on the target queries.

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