Reverse Engineering SGO Success

1. The Challenge

The core question for legacy publishers is no longer “How do I rank #1?” but “How do I become the grounded source for AI Overviews?”. The Spruce Pets provides a masterclass in this transition.

2. Methodology: The Reverse Engineering Process

To analyze this success, I performed a technical audit of the page’s structured data (JSON-LD) to identify hidden “Trust Signals” that Google’s AI prefers:

• Schema Extraction: Isolated the application/ld+json blocks.
• Entity Mapping: Identified how the site connects Content (Article) to Expertise (Person) and Authority (MedicalWebPage).
• Correlation: Looked at how AI Overviews extract steps even without explicit HowTo schema.

3. Key Findings: The “Why” Behind the Ranking

A. The “Reviewer” Moat (EEAT)

Spruce Pets uses a reviewedBy field to create a layer of verification that AI models crave.

• The Data: The schema points to Nick Saint-Erne, a Doctor of Veterinary Medicine (DVM).
• SGO Impact: Google’s AI avoids giving harmful medical advice. By linking to a verified DVM, the content passes the “Safety Filter,” making it eligible for the top AI Overview slot.

B. Semantic Contextualization

The content is dual-typed as Article AND MedicalWebPage.

• The Data: @type: ["Article", "MedicalWebPage"].
• SGO Impact: This tells the AI precisely which “knowledge bucket” to place the information in, ensuring it shows up for high-intent queries like “how to treat fish fungus.”

C. Factual Grounding

The logic isn’t just “Trust us,” it’s “Trust the source.”

• The Data: Inclusion of a citation field linked to the University of Florida (EDU).
• SGO Impact: AI models (like Gemini) value “Grounding.” Providing citable sources in the code helps the AI verify the facts before presenting them to the user.