Google’s AI Overviews, also known as Search Generative Experience (SGE), are reshaping search rankings. Instead of prioritizing keyword-heavy pages, Google now favors deep pages—content that provides comprehensive, structured, and semantically rich information.
This shift means shallow, generic content is becoming less visible, while in-depth, well-researched content is gaining traction. In this guide, we’ll break down what deep pages are, why Google AI prefers them, and how you can structure your content to improve rankings.
What Are Deep Pages in SEO?
A deep page is a high-value content piece that thoroughly covers a specific topic, its sub-entities, and related search intents.
How Deep Pages Differ from Shallow Content
Feature | Deep Page | Shallow Page |
Length | 1,500+ words with structured hierarchy | Short, often under 600 words |
Coverage | Covers all subtopics & angles | Focuses on basic info |
Internal Links | Connects to related, supporting pages | Few or no internal links |
Information Gain | Adds new insights, analysis, & examples | Repeats common knowledge |
Format | Uses FAQs, tables, multimedia, schema | Plain text with little structure |
Attributes of Deep Content
Long-form content (but without fluff)
Covers multiple sub-entities and related questions
Has strong internal contextual connections (links to supportive pages)
Uses structured formatting (H2-H4 hierarchy, FAQs, pros/cons, how-tos)
How Google’s AI Overviews Select Pages
Google’s AI-powered ranking system relies on semantic vectorization, information gain scoring, and neural retrieval models to determine which pages appear in AI Overviews.
Key Factors That Influence AI Overview Selection
EEAT (Experience, Expertise, Authoritativeness, Trustworthiness) → Sites with high topical authority perform better.
Precise answers to sub-intents → Pages must address long-tail and niche queries.
Structured + well-contextualized data → Well-organized content with clear topic clusters gets priority.
Google’s AI Research Confirms This:
- Google’s Information Gain Patent states:
“Pages that introduce new, valuable information beyond what is commonly found in existing indexed documents receive higher relevance scores.” - A Google AI Research Paper explains:
“Semantic vectorization allows the model to retrieve contextually rich documents rather than relying purely on keyword matching.”
Why This Matters? Pages that repeat commonly known facts or lack depth are filtered out, while unique, research-backed content is prioritized.
Why Shallow Content Fails in AI Overviews
Lacks Semantic Relationships → Content that doesn’t connect to related topics or internal links gets ignored.
No Entity Subtopic Coverage → AI prefers deep topic coverage with multiple angles, not just surface-level facts.
Thin Content Doesn’t Get Selected → Articles with low word count and generic advice are deprioritized.
Example:
Shallow Page: “SEO Tips for Beginners” – A generic list with basic suggestions.
Deep Page: “How Semantic Entity Optimization Works in Topical Maps” – Explains entity relationships, practical applications, and use cases.
How to Create Deep Pages That Qualify for AI Overviews
Step-by-Step Guide
1. Start from an Entity (e.g., “Topical Authority”)
Research entity relationships using tools like Google NLP API or InLinks.
2. Use Sub-Intent Analysis
Identify related queries and secondary topics to cover within the content.
3. Apply Semantic Content Layering
Structure content in TOFU (awareness) → MOFU (engagement) → BOFU (conversion) layers.
4. Include Multimedia & Structured Data
Add videos, tables, interactive elements, and schema markup for better AI processing.
5. Use FAQs & Schema for Enhanced AI Recognition
Implement FAQ schema to capture AI-generated snippets and long-tail searches.
Real-World AI Overview Example: Deep vs. Shallow Pages
Case Study: AI Overview Preferring a Deep Page Over a Shallow One
Query: “How does Google’s AI choose search results?”
AI Overview Result (Example of a Deep Page Selected)
- Featured Page: Google’s Neural Ranking Models Explained
- Why It Was Chosen:
- Long-form guide with structured sections
- References Google’s AI patents and papers
- Includes diagrams explaining ranking models
A Shallow Page That Didn’t Get Selected
- Title: How Google Search Works (Basic blog post)
- Why It Was Ignored:
- Thin content (under 800 words)
- No citations or research-backed insights
- No internal linking or supporting subtopics
Key Takeaway: Google’s AI prefers detailed, research-backed content with high information gain, not generic overviews.
Conclusion
Google’s AI Overviews prioritize deep, well-structured content over thin, keyword-stuffed pages. To stay ahead:
Focus on depth, not word count.
Use structured content formatting (H2-H4, FAQs, schema, multimedia).
Leverage entity-based SEO and internal linking for authority transfer.
At Conquerra Digital, we specialize in semantic SEO, topical authority building, and AI-driven content strategies.
Want to optimize your content for Google AI Overviews? Contact Conquerra Digital today!
FAQs: Google AI Overviews & Deep Pages
Not necessarily. Deep pages focus on coverage, structure, and semantic depth—not just word count.
Yes. Expanding old content by adding subtopics, internal links, and structured data can improve its AI Overview ranking potential.
Google identifies relationships between entities in your content. Better entity coverage improves contextual relevance and ranking potential.
Mostly, but not always. Some Overviews still summarize multiple sources, but pages with high information gain and structured data have a better chance of being cited.
Yes. Internal linking reinforces topical authority and helps search engines understand content relationships, making deep pages stronger.
