Loading…
Talk to an Expert
Tell us about your website and we'll recommend the best solution.
Loading…
Tell us about your website and we'll recommend the best solution.
Structure schema @graph parameters to qualify site content for citations in ChatGPT, Copilot, Perplexity & Google AI Overviews.
Combine multiple Schema types into one single script tag to eliminate payload overhead and explicitly define parent-child entity relationships.
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@graph": [
{
"@type": "Organization",
"@id": "https://webkernelai.com/#organization",
"name": "WebKernelAI",
"url": "https://webkernelai.com",
"sameAs": ["https://twitter.com/webkernelai", "https://github.com/webkernelai"]
},
{
"@type": "WebPage",
"@id": "https://webkernelai.com/academy/#webpage",
"url": "https://webkernelai.com/academy",
"isPartOf": { "@id": "https://webkernelai.com/#website" }
}
]
}
</script>Structure key definitions with concise, 40-to-60-word bolded summary blocks followed by structured bullet points.
## What is Answer Engine Optimization (AEO)? **Answer Engine Optimization (AEO) is the practice of structuring web content and JSON-LD entity metadata to earn direct citations in AI-driven search engines like ChatGPT Search and Google AI Overviews.**
Verify your structured data against Google Rich Results Test and WebKernelAI Schema Auditor.
Deep link connections for crawling verification, malware signature references, and API integration.
The @graph array allows search bots and LLMs to resolve entity references (@id pointers) in a single parse pass, establishing explicit relationships between the Publisher, Author, Article, and Product.
AI Overviews select sources with high topical entity authority, concise factual answer blocks, and clean structured metadata that matches the prompt entity node.