Schema markup does not increase rankings on its own, but it helps search engines understand your listings and present them more accurately. Real estate websites perform best when they use multiple schema types together, such as RealEstateListing, property type schemas, Agent, Organization, FAQ, BlogPosting, Video, and Event. JSON-LD is the recommended format because it is easier to manage and keeps structured data separate from your design. The real benefit comes from accuracy and consistency: audit your pages, apply the correct schema, validate everything, and update it as details change. When done correctly, schema improves visibility, strengthens click-through rates, and helps Google match your listings to the right searchers.
Schema markup won't automatically push your listings to the top of Google. And it definitely won't replace quality content or solid backlink strategy.
What it will do is help search engines understand exactly what your content represents.
When Google knows that a page is an active real estate listing with specific attributes, tied to a verified agent at a recognized brokerage, it can index, categorize, and serve that content more effectively to relevant searches.
This guide breaks down exactly which schema types matter for real estate, how they work together, what results you can actually expect, and how to implement them without getting overwhelmed by technical jargon or unrealistic promises.
Schema markup is structured data code written in JSON-LD that you add to your website to help search engines understand exactly what your content is about.
It acts as a bridge between your property listings and Google’s algorithms, which is essential for strong local real estate SEO.
When you list a property at "123 Main Street" on your website, search engines see text. But when you add schema markup, they see a structured property listing with a specific address, price, square footage, and number of bedrooms.
These markups help turn text into Things by establishing relationships between your content elements and recognized entities in Google's knowledge graph.
Schema markup is the code you add to your website, while rich results are what appears in search results when that code works properly.
Schema markup doesn't guarantee rich results, but it makes them possible.
Schema markup serves three critical functions for real estate websites.
When you implement schema markup correctly, you're not just hoping Google understands your content, you're giving them exactly what they need to showcase your properties to potential buyers actively searching for homes.
Here's what separates amateur real estate SEO from professional implementation: knowing which schema types to use and when.
Real estate websites need multiple schema types working together.
A single property listing might use three or four different schemas to fully communicate its details to search engines. A comprehensive strategy includes property schemas, agent schemas, organizational markup, and content schemas, each serving a specific purpose in your overall visibility.
The RealEstateListing schema is your primary weapon for property visibility. This schema type is specifically designed for real estate and includes properties like listing price, date listed, property type, address, and listing status.
Use this schema on every individual property listing page. It tells search engines: "This is an active real estate listing" and provides structured information about price ranges, location details, property features, and availability status.
The key properties you should always include are the listing type (sale or rental), price or price range, address with full postal details, and property category (residential, commercial, land). Smart agents also include lease length for rentals, year built, and square footage when available.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "RealEstateListing",
"name": "Beautiful 3-Bedroom Home in Arlington Heights",
"url": "https://www.yourwebsite.com/listings/123-main-street",
"description": "Stunning renovated home with modern kitchen, hardwood floors, and large backyard perfect for entertaining.",
"datePosted": "2024-11-15",
"validThrough": "2025-05-15",
"address": {
"@type": "PostalAddress",
"streetAddress": "123 Main Street",
"addressLocality": "Arlington Heights",
"addressRegion": "IL",
"postalCode": "60004",
"addressCountry": "US"
},
"price": "450000",
"priceCurrency": "USD",
"availableAtOrFrom": {
"@type": "Place",
"address": {
"@type": "PostalAddress",
"streetAddress": "123 Main Street",
"addressLocality": "Arlington Heights",
"addressRegion": "IL",
"postalCode": "60004"
}
}
}
</script>
While RealEstateListing tells search engines it's a property for sale, SingleFamilyResidence tells them what type of property it is.
This schema includes detailed specifications unique to single-family homes, number of bedrooms and bathrooms, parking capacity, property size, and lot dimensions.
Use SingleFamilyResidence in combination with RealEstateListing on home pages. This layered approach gives search engines both the listing context and the specific property details they need to match your listing with relevant searches.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "SingleFamilyResidence",
"name": "Beautiful 3-Bedroom Home in Arlington Heights",
"address": {
"@type": "PostalAddress",
"streetAddress": "123 Main Street",
"addressLocality": "Arlington Heights",
"addressRegion": "IL",
"postalCode": "60004",
"addressCountry": "US"
},
"numberOfRooms": 8,
"numberOfBedrooms": 3,
"numberOfBathroomsTotal": 2,
"floorSize": {
"@type": "QuantitativeValue",
"value": 2100,
"unitCode": "FTK"
},
"yearBuilt": 1985,
"numberOfParkingSpaces": 2,
"amenityFeature": [
{
"@type": "LocationFeatureSpecification",
"name": "Hardwood Floors",
"value": true
},
{
"@type": "LocationFeatureSpecification",
"name": "Central Air Conditioning",
"value": true
},
{
"@type": "LocationFeatureSpecification",
"name": "Fireplace",
"value": true
}
]
}
</script>
The Apartment schema serves the same purpose as SingleFamilyResidence but for multi-unit dwellings. It includes properties specific to apartment living, floor level, pet policies, amenities, and lease terms.
The difference between Apartment and ApartmentComplex schemas is crucial: Apartment is for a specific unit, while ApartmentComplex (which we'll cover next) is for the entire property.
Include unit-specific details like floor plan type, square footage, number of occupants allowed, lease duration, and included utilities.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Apartment",
"name": "Modern 2-Bedroom Apartment - Unit 304",
"address": {
"@type": "PostalAddress",
"streetAddress": "456 Park Avenue, Unit 304",
"addressLocality": "Chicago",
"addressRegion": "IL",
"postalCode": "60611",
"addressCountry": "US"
},
"numberOfRooms": 5,
"numberOfBedrooms": 2,
"numberOfBathroomsTotal": 2,
"floorSize": {
"@type": "QuantitativeValue",
"value": 1200,
"unitCode": "FTK"
},
"floorLevel": "3",
"occupancy": {
"@type": "QuantitativeValue",
"maxValue": 4
},
"petsAllowed": "Dogs and cats under 25 lbs allowed",
"amenityFeature": [
{
"@type": "LocationFeatureSpecification",
"name": "In-Unit Washer/Dryer",
"value": true
},
{
"@type": "LocationFeatureSpecification",
"name": "Balcony",
"value": true
},
{
"@type": "LocationFeatureSpecification",
"name": "Stainless Steel Appliances",
"value": true
}
],
"leaseLength": {
"@type": "QuantitativeValue",
"value": 12,
"unitCode": "MON"
}
}
</script>
ApartmentComplex schema marks up entire multi-unit properties rather than individual units.
This schema includes properties like total number of units, available amenities, contact information, and general pricing ranges.
Use this schema onlanding pages for apartment buildings or complexes. It's perfect for property management companies managing multiple units within a single location.
The key distinction here is scale.
While individual Apartment schemas handle unit-specific details, ApartmentComplex communicates building-wide information, pool facilities, parking structures, pet policies, and community amenities that apply across all units.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "ApartmentComplex",
"name": "Lakeside Towers Apartments",
"address": {
"@type": "PostalAddress",
"streetAddress": "456 Park Avenue",
"addressLocality": "Chicago",
"addressRegion": "IL",
"postalCode": "60611",
"addressCountry": "US"
},
"telephone": "+1-312-555-0199",
"email": "leasing@lakesidetowers.com",
"url": "https://www.lakesidetowers.com",
"numberOfAccommodationUnits": 150,
"petsAllowed": "Dogs and cats under 25 lbs allowed with deposit",
"amenityFeature": [
{
"@type": "LocationFeatureSpecification",
"name": "Fitness Center",
"value": true
},
{
"@type": "LocationFeatureSpecification",
"name": "Rooftop Pool",
"value": true
},
{
"@type": "LocationFeatureSpecification",
"name": "24-Hour Concierge",
"value": true
},
{
"@type": "LocationFeatureSpecification",
"name": "Parking Garage",
"value": true
},
{
"@type": "LocationFeatureSpecification",
"name": "Business Center",
"value": true
}
],
"geo": {
"@type": "GeoCoordinates",
"latitude": "41.8919",
"longitude": "-87.6270"
}
}
</script>
The RealEstateAgent schema puts your professional profile into search engines' structured data.
This schema includes your name, credentials, license information, areas served, and specializations.
Use it on your bio page, about us page, team page, or anywhere your professional profile appears on your website.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "RealEstateAgent",
"name": "Sarah Mitchell",
"url": "https://www.yourwebsite.com/agents/sarah-mitchell",
"image": "https://www.yourwebsite.com/images/sarah-mitchell.jpg",
"telephone": "+1-847-555-0123",
"email": "sarah@yourwebsite.com",
"address": {
"@type": "PostalAddress",
"streetAddress": "789 Business Plaza, Suite 200",
"addressLocality": "Arlington Heights",
"addressRegion": "IL",
"postalCode": "60005",
"addressCountry": "US"
},
"areaServed": [
{
"@type": "City",
"name": "Arlington Heights"
},
{
"@type": "City",
"name": "Palatine"
},
{
"@type": "City",
"name": "Mount Prospect"
}
],
"knowsLanguage": ["English", "Spanish"],
"memberOf": {
"@type": "Organization",
"name": "National Association of Realtors"
}
}
</script>
The Person schema complements RealEstateAgent by adding broader professional and personal details that don't fit in the real estate-specific schema.
This includes your educational background, awards, social media profiles, and professional images.
Layer Person schema with RealEstateAgent schema on profile pages. Together, they create a comprehensive professional profile that search engines can fully understand and potentially display in knowledge panels or enhanced search results.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Person",
"name": "Sarah Mitchell",
"url": "https://www.yourwebsite.com/agents/sarah-mitchell",
"image": "https://www.yourwebsite.com/images/sarah-mitchell.jpg",
"jobTitle": "Senior Real Estate Agent & Buyer Specialist",
"telephone": "+1-847-555-0123",
"email": "sarah@yourwebsite.com",
"worksFor": {
"@type": "Organization",
"name": "Premier Realty Group"
},
"alumniOf": {
"@type": "EducationalOrganization",
"name": "University of Illinois"
},
"award": [
"Top Producer 2023",
"Five Star Professional 2022-2024"
],
"sameAs": [
"https://www.linkedin.com/in/sarahmitchell",
"https://www.facebook.com/sarahmitchellrealtor",
"https://www.instagram.com/sarahmitchellhomes"
],
"knowsAbout": [
"Residential Real Estate",
"First-Time Home Buyers",
"Luxury Properties",
"Investment Properties"
]
}
</script>
Your brokerage or agency needs markup too. Organization schema structures your company information, legal name, address, logo, contact details, and areas of service.
Implement Organization schema on your homepage, about page, and contact page. This schema establishes your business entity in search engines' understanding and is crucial for local SEO and Google Business Profile integration.
Key properties include your official business name, complete address with geographic coordinates, company logo, telephone number, email address, and social media profiles.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "RealEstateAgent",
"name": "Premier Realty Group",
"url": "https://www.premierrealtygroup.com",
"logo": "https://www.premierrealtygroup.com/images/logo.png",
"image": "https://www.premierrealtygroup.com/images/office.jpg",
"description": "Full-service real estate brokerage serving the Chicago Northwest suburbs with over 25 years of experience.",
"address": {
"@type": "PostalAddress",
"streetAddress": "789 Business Plaza, Suite 200",
"addressLocality": "Arlington Heights",
"addressRegion": "IL",
"postalCode": "60005",
"addressCountry": "US"
},
"geo": {
"@type": "GeoCoordinates",
"latitude": "42.0883",
"longitude": "-87.9806"
},
"telephone": "+1-847-555-0100",
"email": "info@premierrealtygroup.com",
"priceRange": "$$",
"openingHoursSpecification": [
{
"@type": "OpeningHoursSpecification",
"dayOfWeek": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"],
"opens": "09:00",
"closes": "18:00"
},
{
"@type": "OpeningHoursSpecification",
"dayOfWeek": "Saturday",
"opens": "10:00",
"closes": "16:00"
}
],
"sameAs": [
"https://www.facebook.com/premierrealtygroup",
"https://www.linkedin.com/company/premier-realty-group",
"https://www.instagram.com/premierrealtygroup"
],
"areaServed": [
"Arlington Heights, IL",
"Palatine, IL",
"Mount Prospect, IL",
"Schaumburg, IL"
]
}
</script>
Event schema is designed for open houses, property tours, first-time homebuyer seminars, and any real estate-related events you host.
It includes start and end times, location details, registration information, and event descriptions.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Event",
"name": "Open House - 123 Main Street",
"description": "Join us for an open house at this beautiful 3-bedroom home in Arlington Heights. Tour the property, ask questions, and learn about the neighborhood.",
"startDate": "2024-12-14T13:00:00-06:00",
"endDate": "2024-12-14T15:00:00-06:00",
"eventStatus": "https://schema.org/EventScheduled",
"eventAttendanceMode": "https://schema.org/OfflineEventAttendanceMode",
"location": {
"@type": "Place",
"name": "123 Main Street",
"address": {
"@type": "PostalAddress",
"streetAddress": "123 Main Street",
"addressLocality": "Arlington Heights",
"addressRegion": "IL",
"postalCode": "60004",
"addressCountry": "US"
}
},
"image": "https://www.yourwebsite.com/listings/123-main-street/photos/front.jpg",
"organizer": {
"@type": "RealEstateAgent",
"name": "Sarah Mitchell",
"telephone": "+1-847-555-0123",
"email": "sarah@yourwebsite.com",
"url": "https://www.yourwebsite.com/agents/sarah-mitchell"
},
"offers": {
"@type": "Offer",
"url": "https://www.yourwebsite.com/listings/123-main-street",
"price": "0",
"priceCurrency": "USD",
"availability": "https://schema.org/InStock",
"validFrom": "2024-11-15T00:00:00-06:00"
}
}
</script>
FAQPage schema structures your frequently asked questions so they can appear as rich results directly in search.
Use FAQPage schema on property detail pages with common questions, neighborhood guides with local FAQs, and dedicated FAQ sections addressing buyer or seller concerns.
Include questions about property specifics, neighborhood details, buying processes, and financing options relevant to your listings.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "What is included in the sale of 123 Main Street?",
"acceptedAnswer": {
"@type": "Answer",
"text": "The sale includes all kitchen appliances (refrigerator, dishwasher, range, and microwave), washer and dryer, window treatments throughout, the shed in the backyard, and all lighting fixtures. The home also comes with a one-year home warranty for added peace of mind."
}
},
{
"@type": "Question",
"name": "What are the property taxes for this home?",
"acceptedAnswer": {
"@type": "Answer",
"text": "The current annual property taxes are approximately $8,200. This is based on the most recent tax year. Property taxes in Arlington Heights are subject to change based on assessments and local tax rates."
}
},
{
"@type": "Question",
"name": "What school district is this property in?",
"acceptedAnswer": {
"@type": "Answer",
"text": "This home is located in Arlington Heights School District 25 for elementary and middle school, and Township High School District 214 for high school. The assigned schools are Thomas Middle School and Hersey High School, both of which have excellent ratings."
}
},
{
"@type": "Question",
"name": "Is the basement finished?",
"acceptedAnswer": {
"@type": "Answer",
"text": "Yes, the basement is fully finished with a family room, full bathroom, and additional bedroom. The basement also includes a utility room with the furnace, water heater, and plenty of storage space."
}
}
]
}
</script>
Your real estate blog posts deserve structured data too. BlogPosting schema tells search engines exactly what each article is about, who wrote it, when it was published, and what topics it covers.
Implement BlogPosting schema on every article in your real estate blog, market updates, neighborhood guides, home buying tips, and property spotlights.
This schema includes properties like headline, author, publication date, featured image, and article body.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "BlogPosting",
"headline": "Arlington Heights Real Estate Market Update - December 2024",
"alternativeHeadline": "What Buyers and Sellers Need to Know About Arlington Heights Home Prices",
"image": "https://www.yourwebsite.com/blog/images/arlington-market-dec-2024.jpg",
"author": {
"@type": "Person",
"name": "Sarah Mitchell",
"url": "https://www.yourwebsite.com/agents/sarah-mitchell"
},
"publisher": {
"@type": "Organization",
"name": "Premier Realty Group",
"logo": {
"@type": "ImageObject",
"url": "https://www.premierrealtygroup.com/images/logo.png"
}
},
"datePublished": "2024-12-04",
"dateModified": "2024-12-04",
"description": "Comprehensive analysis of the Arlington Heights real estate market including median home prices, inventory levels, days on market, and predictions for 2025.",
"articleBody": "The Arlington Heights real estate market continues to show resilience...",
"url": "https://www.yourwebsite.com/blog/arlington-heights-market-update-december-2024",
"mainEntityOfPage": {
"@type": "WebPage",
"@id": "https://www.yourwebsite.com/blog/arlington-heights-market-update-december-2024"
},
"keywords": [
"Arlington Heights real estate",
"home prices Arlington Heights",
"real estate market update",
"buying a home Arlington Heights"
]
}
</script>
Video schema marks up your virtual tours, property walkthroughs, and real estate educational content with structured information about duration, upload date, description, and thumbnail.
Use Video schema on property pages with virtual tours, YouTube embeds on your website, and dedicated video gallery pages. Include properties like video name, description, thumbnail URL, upload date, and content URL.
JSON-LD Code Example:
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "VideoObject",
"name": "Virtual Tour - 123 Main Street, Arlington Heights",
"description": "Take a complete virtual tour of this stunning 3-bedroom home in Arlington Heights featuring hardwood floors, renovated kitchen, and beautiful backyard. See every room and all the amazing features this property has to offer.",
"thumbnailUrl": "https://www.yourwebsite.com/listings/123-main-street/video-thumbnail.jpg",
"uploadDate": "2024-11-20T08:00:00-06:00",
"duration": "PT3M45S",
"contentUrl": "https://www.yourwebsite.com/videos/123-main-street-tour.mp4",
"embedUrl": "https://www.youtube.com/embed/abc123xyz",
"publisher": {
"@type": "Organization",
"name": "Premier Realty Group",
"logo": {
"@type": "ImageObject",
"url": "https://www.premierrealtygroup.com/images/logo.png"
}
},
"potentialAction": {
"@type": "SeekToAction",
"target": "https://www.yourwebsite.com/videos/123-main-street-tour.mp4?t={seek_to_second_number}",
"startOffset-input": "required name=seek_to_second_number"
}
}
</script>
Most real estate agents stumble at implementation not because it's technically impossible, but because they don't have a clear roadmap. Here's the step-by-step process that takes you from zero schema to fully validated structured data.
Start by identifying every page type on your website that needs schema markup. Property listings need RealEstateListing schema, agent profiles need RealEstateAgent and Person schemas, your blog posts need BlogPosting schema, and your homepage needs Organization schema.
Create a simple spreadsheet listing each page type, the primary schema it requires, and any secondary schemas you'll layer on top.
You'll need to decide how you want to write your structured data. JSON-LD is Google's recommended format and the easiest to implement, but understanding your options helps you make an informed choice.
For each page type identified in your audit, create the appropriate schema markup. Start with your highest-traffic pages, typically property listings and your homepage, then work through agent profiles and blog content.
Use the examples provided earlier in this guide as templates, but customize every property to match your actual content. Generic schema that doesn't match your page content is worse than no schema at all.
The implementation location depends on your website platform. For custom-built sites, add JSON-LD code to the head section of each page template.
Most modern real estate platforms include custom code sections specifically designed for schema markup. IDX sites may require coordination with your provider to ensure schema appears on all listing pages.
Never deploy schema markup without validation. Run every page through multiple validators to catch syntax errors, missing required properties, and logic issues that would prevent search engines from understanding your structured data.
Use Schema.org's validator first to check basic compliance, then Google's Rich Results Test to verify rich result eligibility, then Classy Schema for detailed error analysis.
Schema markup isn't set-it-and-forget-it. When property prices change, listing statuses update, or agents join or leave your brokerage, your schema needs updating too.
Set a monthly reminder to review your most important pages and verify schema accuracy.
Pay special attention to active listings where price reductions or status changes require immediate schema updates.
While most guides focus exclusively on JSON-LD, understanding all three schema formats helps you make informed decisions about implementation and troubleshoot issues when working with different platforms.
JSON-LD is JavaScript Object Notation for Linked Data, and it's the format Google explicitly recommends for structured data implementation.
The primary advantage is separation of concerns. JSON-LD sits in a script tag in your page's head section, completely separate from your visible HTML content.
This means you can add, edit, or remove schema markup without touching your page design or risking breaking your layout.
Microdata embeds schema markup directly into your HTML tags using attributes like itemscope, itemtype, and itemprop. Instead of separate structured data code, you're adding attributes to the HTML elements that display your content.
Here's what that looks like for a simple property address:
<div itemscope itemtype="https://schema.org/RealEstateListing">
<span itemprop="name">Beautiful Home in Arlington Heights</span>
<div itemprop="address" itemscope itemtype="https://schema.org/PostalAddress">
<span itemprop="streetAddress">123 Main Street</span>
<span itemprop="addressLocality">Arlington Heights</span>
<span itemprop="addressRegion">IL</span>
</div>
</div>
The advantage of Microdata is direct correspondence between visible content and structured data. What users see is exactly what search engines interpret, reducing the risk of schema-content mismatches.
The disadvantage is maintenance complexity. Every time you update your page design or content structure, you're also potentially updating schema markup.
For real estate websites with dynamic listing content, this creates ongoing technical debt.
RDFa is Resource Description Framework in Attributes, another method of embedding structured data directly into HTML. It's similar to Microdata but uses different attribute names like vocab, typeof, and property.
Here's the same property address in RDFa:
<div vocab="https://schema.org/" typeof="RealEstateListing">
<span property="name">Beautiful Home in Arlington Heights</span>
<div property="address" typeof="PostalAddress">
<span property="streetAddress">123 Main Street</span>
<span property="addressLocality">Arlington Heights</span>
<span property="addressRegion">IL</span>
</div>
</div>
RDFa offers more flexibility than Microdata for complex semantic relationships and was originally developed for the semantic web. Some content management systems favor RDFa because it integrates with their existing infrastructure.
For real estate websites specifically, RDFa has limited advantages over JSON-LD and shares Microdata's maintenance challenges.
JSON-LD is the clear winner. Google recommends it, it's easier to implement and maintain, it separates structured data from page design, and it handles complex nested schemas more elegantly.
The only scenario where alternative formats make sense is when your platform enforces a different approach.
The manual process of writing schema markup from scratch intimidates most agents, which is why generation tools exist.
Here's what I tell agents, automated tools are starting points, not finished solutions.
The limitation with standard generators is their generic approach. They don't understand the nuances of real estate schema or how to layer multiple schema types for maximum impact.
Cursor is an AI-powered code editor that can reference the entire Schema.org knowledge base while generating custom schema markup for your specific properties.
Instead of using a template generator that knows nothing about your three-bedroom Victorian with original crown molding, you're working with AI that understands both schema structure and your unique property details.
The advantage is customization at scale. You can generate highly specific schema markup for unusual property types, layer multiple schemas intelligently, and include niche properties that generic generators ignore.
The ultimate control comes from writing schema markup manually, directly from Schema.org documentation. This approach requires understanding JSON-LD syntax and the specific properties available for each schema type.
When is manual writing necessary?
When you have highly unusual properties, when you're implementing complex nested schemas, or when automated tools consistently produce errors in their output.
The skills required include
The benefit is complete control, you include exactly the properties you want, structure nested schemas precisely, and create implementations that perfectly match your content.
Validation checks your schema markup for syntax errors, incorrect property types, and logic issues that would prevent search engines from understanding your structured data.
Before deploying any schema markup to your live real estate website, run it through multiple validators.
Each validator catches different issues, and using several ensures comprehensive error detection.
The Schema.org validator is your first line of defense. This official tool checks whether your schema markup follows the Schema.org specification, proper syntax, valid property names, correct nesting structure, and appropriate property types.
Access it directly on Schema.org's website. Paste your schema markup code into the validator, and it returns a detailed report highlighting any errors or warnings.
Google's Rich Results Test serves a different purpose than general schema validation. This tool specifically checks whether your schema markup qualifies for rich results in Google Search.
Here's the critical distinction: valid schema doesn't guarantee rich results. Google has additional requirements beyond basic validity, certain required properties, content guidelines, and quality standards that determine rich result eligibility.
Run your property page URLs through this validator to see both the structured data Google detects and whether that data meets rich result requirements.
Classy Schema offers more detailed error reporting and additional insights beyond basic syntax validation. This third-party validator provides clearer explanations of errors, context-aware suggestions for fixes, and warnings about properties that could be improved even when not technically errors.
It catches edge cases that other validators miss and provides the clearest explanations for fixing complex errors.
Here's the reality check most agents need: increased visibility from schema markup means nothing if you can't convert that traffic into actual client relationships.
This is where I see the biggest gap. Agents implement perfect schema markup, watch their search visibility improve, see traffic increase, and then lose those visitors because their website has no systematic lead capture strategy.
Madison is designed specifically to bridge this gap.
Don't let another potential client walk away because you weren't available to respond instantly. Madison's pricing is designed to pay for itself with just one additional deal per month.
Before you spend another dollar on marketing that doesn't convert, take 2 minutes to see how Madison turns your existing website traffic into a steady stream of qualified appointments.
Within just a few months, Realty AI helped Team Logue capture 15 high-quality leads, resulting in 3 new transactions worth over $3.3 million. This success generated an estimated $82,500–$95,000 in gross commission income (GCI).
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