Structured data markup for video content enabling video rich results with thumbnails, duration, and upload date in search.
Video Schema is structured data markup that provides search engines with detailed information about video content, including metadata like duration, thumbnail URL, upload date, and description. This markup enables videos to appear with enhanced rich results in search, displaying visual previews and key details directly in the SERPs rather than as plain text links.
The markup follows Schema.org standards and is typically implemented using JSON-LD format. When properly configured, video schema transforms how your video content appears in search results, making it more visually appealing and informative to users browsing search results pages.
Why It Matters for AI SEO
AI-powered search systems increasingly prioritize multimedia content, and video schema serves as a critical bridge between your video content and these intelligent systems. Google's AI algorithms use structured data to better understand video context, enabling more accurate matching between user queries and video content. This becomes particularly important as search experiences evolve to include video carousels, AI Overviews that reference video content, and multimodal search results. Modern AI systems can process video schema alongside visual analysis of the actual video content, creating a more comprehensive understanding of the material. This dual approach helps AI determine when to surface videos for specific queries, whether in traditional search results or emerging formats like AI-generated summaries.
How It Works
Video schema implementation requires several key properties: name, description, thumbnailUrl, uploadDate, duration, and contentUrl. The markup should be placed in the HTML head or body of pages containing video content. Essential properties like duration must be formatted correctly (ISO 8601 format), and thumbnail URLs should point to high-quality images that accurately represent the video content. Tools like Schema Pro and Google's Rich Results Test help validate implementation and preview how results will appear. The markup works for embedded videos, hosted videos, and even links to external platforms like YouTube, though hosted content typically performs better for rich results eligibility.
Common Mistakes
Many implementations fail because they use placeholder or generic thumbnails instead of actual video thumbnails, which prevents rich results from displaying. Another frequent error is incorrect duration formatting - using simple numbers instead of ISO 8601 duration format (PT1M30S for 1 minute 30 seconds). Missing required properties like uploadDate or using broken URLs for video content also prevents successful rich results display, even when the markup validates syntactically.