Case study: improving SEO metadata with Open Graph and structured data implementation

Case study: improving SEO metadata with Open Graph and structured data implementation

Issue background

A major food blog sought to enhance its SEO and social media presentation by improving how articles appeared when shared across platforms like Facebook, X (Twitter), and Pinterest.

Although the site already included basic meta tags, the Open Graph (OG) data was incomplete and inconsistent, especially for image dimensions and author details. Additionally, the site lacked proper Article JSON-LD schema, which helps Google identify and display content more effectively in search results and Google Discover.

The project’s goal was to ensure full compliance with both Open Graph and Google’s structured data guidelines — improving discoverability, share previews, and content authority.

Diagnosis

Freshy’s development team performed a full audit of the site’s head metadata and structured data output. The findings included:

• Missing image width, image height, and image type tags.
• Incorrect author tag format — using a nonstandard property instead of article:author.
• No Article JSON schema, resulting in Google ignoring key publication details.
• Schema inconsistencies between content types — homepage, category pages, and single posts.
• Some JSON-LD outputs were valid JSON but not recognized by Google’s Rich Results Test, due to unsupported schema types (WebPage, CollectionPage, etc.).

The challenge was to introduce a unified, valid schema system that applied context-specific structured data while keeping the site’s lightweight Thesis-based architecture intact.

Resolution steps

Freshy implemented a multi-layered SEO enhancement process, balancing compliance with performance:

1. Open Graph optimization
   Added missing OG meta tags for:

   <meta property="og:image:type" content="image/jpeg" />
   <meta property="og:image:width" content="1200" />
   <meta property="og:image:height" content="630" />
   <meta property="article:author" content="https://inspiredtaste.net/author/adam-and-joanne/" />

   Standardized the meta tag format across posts, categories, and pages, confirming image dimensions and file types matched social platform requirements.

2. Article JSON-LD schema integration
   Added a new PHP function add_json_schema_to_head() to dynamically inject JSON-LD based on page context. Applied Google’s recommended schema fields, including:
   • @context, @type, headline, image, author, datePublished, dateModified, and publisher.

   Used conditional logic for different content types:
   Post → Article
   Page → WebPage
   Front Page → WebSite
   Category → CollectionPage

3. Schema debugging and refinement
   Validated output in both Schema.org Validator and Google’s Rich Results Test. Fixed issues with escaping slashes (WordPress default behavior) and missing descriptions. Added unique @id fields for each page type (e.g., #article for single posts) to ensure clarity for crawlers. Tested schema consistency on staging before pushing live.
4. Simplification and performance tuning
   Streamlined schema to focus on Article type only for now, since Google doesn’t index additional schema types like WebPage or CollectionPage for rich results. Ensured the JSON was generated inline rather than loaded from external files to preserve page speed.
5. Deployment and validation
   Deployed the improvements to production, verified successful parsing through Google’s testing tools, and maintained a future plan for adding organization-level schema (Organization and WebSite) once further validation is complete.

Final outcome

After the update, the site’s articles now feature:

• Fully compliant Open Graph metadata that displays correct author, image, and sizing information across all social platforms.
• Valid, Google-recognized Article JSON schema with proper publishing and author data.
• Cleaner, more consistent metadata across all post types, improving crawlability and SERP appearance.
• Optimized metadata hierarchy without adding unnecessary plugins or code bloat.

The result was a lean, standards-compliant metadata system that improved both the site’s search visibility and social media presentation — while remaining compatible with its existing Thesis framework.

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