Enhancing Content Discoverability for AI

Making content easily discoverable for AI search engines is crucial for broader reach. Here's how we improved the accessibility of our tenant portfolio content.

The Goal

Our primary objective was to enable AI search engines to easily discover and consume tenant portfolio content. This involved providing machine-readable endpoints that expose content in a structured and easily parsable manner.

Implementation Details

We focused on providing several key endpoints:

• Structured Data Enhancement: Upgraded structured data markup to provide richer metadata. This allows AI models to better understand the content's context and relevance.

• Standard Format Export: Created a specific endpoint to list all content URLs that are relevant for indexing. This endpoint uses a simple format that makes it easy for AI crawlers to identify and access relevant pages.

• Markdown Post Views: Ensured that content can be accessed in a plain markdown format. This simplifies content extraction and parsing.

Example of structured data enhancement:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "BlogPosting",
  "headline": "Example Blog Post",
  "description": "An example blog post for demonstration purposes.",
  "author": {
    "@type": "Organization",
    "name": "Example Company"
  },
  "datePublished": "2024-01-01"
}
</script>

Benefits

By implementing these changes, we aim to achieve:

• Improved content indexing by AI search engines.
• Increased visibility of tenant portfolio content.
• Better understanding of content context by AI models.

Conclusion

Providing AI-friendly endpoints is essential for maximizing content discoverability. By focusing on structured data and standardized formats, we make it easier for AI systems to access and understand our content, leading to broader reach and greater impact.