How to Use the Spatial Entity Metadata Builder
Generate the HTML metadata that allows 3D objects on your web page to appear in AR search results. This tool produces schema.org markup, meta tags, and a model-viewer embed code optimized for 2026 spatial search engines.
Step 1: Enter the 3D object name, description, and physical dimensions (width, height, depth in meters).
Step 2: Provide the URL to your USDZ or GLTF model file. USDZ is required for Apple AR Quick Look. GLTF works on Android and WebXR.
Step 3: Select the product category and click "Generate Metadata." The tool outputs a complete HTML block including meta tags, JSON-LD schema, and a model-viewer web component.
Paste the generated code into your page's head section and body. When someone searches for your product type using AR-enabled devices (smart glasses, phones with AR browsers), your 3D model will be eligible to appear in spatial search results.
Spatial SEO: The Next Frontier of Search Optimization
Search is moving off the screen and into the physical world. In 2026, an estimated 180 million people use AR-enabled devices for product discovery. When someone points their smart glasses at an empty corner of their living room and asks "Show me a modern bookshelf that fits here," the search engine needs to know which 3D models exist, what their physical dimensions are, and how to render them in the user's space. Traditional HTML meta tags do not carry this information. Spatial metadata does.
What Are Spatial Entities?
A spatial entity is a digital representation of a physical object that includes its geometry, dimensions, material properties, and placement context. When you mark up a product page with spatial metadata, you are telling search engines: "This page contains a 3D model of a specific object. Here are its physical dimensions. Here is the file format. Here is how it should be categorized." Search engines that support spatial search (Google, Apple, and several AR-specific platforms) use this metadata to index your 3D content and surface it in AR search results.
The USDZ and GLTF Formats
USDZ (Universal Scene Description, Zipped) is Apple's preferred format for AR content. It is required for AR Quick Look on iOS devices. GLTF (Graphics Language Transmission Format) is the open standard supported by Google, Samsung, and most WebXR implementations. For maximum reach, you should provide both formats. The generated metadata includes a link tag for USDZ and a model-viewer component that automatically selects the best format for the user's device.
Schema.org and 3DModel
The schema.org vocabulary includes a 3DModel type that describes three-dimensional content. The tool generates a complete JSON-LD block using this type, including the encoding format, content URL, spatial coverage, and physical dimensions as additional properties. This structured data helps search engines understand your 3D content without having to parse the model file itself.
Frequently Asked Questions
Yes. This tool generates the metadata and embed code, but you need an actual 3D model file (USDZ or GLTF). You can create these using tools like Blender, Reality Composer, or by converting existing 3D files with Apple's USDZ converter. Several 3D scanning apps can also generate models from physical objects using your phone's camera.
No. Any web page that contains 3D content can benefit from spatial metadata. This includes architectural visualizations, educational models, museum exhibits, real estate tours, and interactive product demos. If your content has a physical dimension, spatial metadata makes it discoverable in AR search.
Model-viewer is an open-source web component developed by Google that renders 3D models in the browser with AR support. It handles device detection, format selection, and AR session management automatically. The generated code includes a model-viewer tag that works on desktop (with orbit controls), iOS (with AR Quick Look), and Android (with Scene Viewer).