GEO Signals: Reference Guide
Core Signals
Structural and content signals that apply to every page type.
AI Bot Access via robots.txt
Allowing AI crawlers (GPTBot, ClaudeBot, PerplexityBot) to index and cite your content.
Author Attribution
A visible author byline with name, credentials, and schema markup identifying who wrote the content.
Authority References
Outbound links to high-authority domains (.gov, .edu, Wikipedia, major publishers) that anchor your claims.
Case Studies
Real-world examples showing measurable results that AI engines use to answer "does X work?" queries.
Clear Takeaway / Key Summary
An explicit summary section that surfaces the page's conclusion for AI extraction.
Comparison Content
A section comparing your product to alternatives, addressing "what is the best X" queries directly.
Content Freshness
A visible publication or last-modified date that lets AI engines assess whether the information is current.
Specific Data & Statistics
Concrete numbers, percentages, and measurable claims that give AI engines verifiable facts to cite.
External References
Outbound links to credible external sources that support your claims.
FAQ Blocks for AI Citability
A dedicated question-and-answer section that AI engines can extract and surface directly.
Heading Hierarchy
Using H1 → H2 → H3 to structure content into scannable, topic-segmented sections.
Images with Descriptive Alt Text
Relevant images with alt text that reinforces the page's topic and entities.
Intro Summary
A concise opening paragraph (under 80 words) that states what the page is about and who it's for.
List Formatting
Bullet or numbered lists that present information in a structure AI engines can extract cleanly.
llms.txt
A plain-text file at /llms.txt that tells AI crawlers what your site is about and what they may use.
On-Page Reviews & Ratings
Customer reviews and aggregate ratings directly embedded on the product page.
Pricing Visibility
Clear, machine-readable pricing on the page that AI shopping assistants can extract.
Product Schema
schema.org/Product markup that makes product details machine-readable for AI shopping assistants.
Schema Markup for AI Engines
JSON-LD structured data that tells AI crawlers what type of content a page contains.
Social Proof
Quantified indicators of adoption — customer count, logos, industry recognition — that establish credibility.
Structured Comparison Tables
HTML tables that present comparative or structured data AI engines can extract as facts.
Testimonials
Named client quotes with attribution that provide social proof and human credibility signals.
Use Cases
Explicit statements of who the product is for and what problems it solves.
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