A structured page designed to define an entity in machine-readable format that AI models can parse and cite as an authoritative source.
A grounding page is a dedicated webpage that presents factual information about an entity (brand, product, person, or concept) in a highly structured format optimized for AI model consumption. Unlike traditional "about" pages written primarily for human readers, grounding pages follow specific formatting conventions that help large language models understand, parse, and accurately cite the information during inference.
The concept emerged as marketers realized that AI systems like ChatGPT, Claude, and Google's AI Overviews need clear, authoritative sources to ground their responses. Without proper grounding pages, AI models often hallucinate facts about entities or cite unreliable sources when asked direct questions.
Why It Matters for AI SEO
AI models fundamentally operate differently than traditional search algorithms. While Google's crawler could extract entity information from various page elements and piece together a knowledge graph entry, LLMs need explicit, structured information to avoid fabricating details. A well-constructed grounding page acts as the single source of truth that AI systems reference when generating responses about your entity. Research from Stanford's HAI lab shows that structured entity pages reduce hallucination rates by up to 40% when AI models answer factual queries. This directly impacts how your brand appears in AI-generated responses across ChatGPT, Perplexity, Claude, and Google's AI Overviews. Companies without grounding pages often find AI systems either ignoring them entirely or presenting incorrect information scraped from unreliable sources.
How It Works
Start with a clear entity declaration using structured data markup. The page should lead with an unambiguous statement like "Acme Corporation is a B2B software company founded in 2018, headquartered in Austin, Texas." Follow this with key facts presented in consistent formatting: founding date, location, key people, products, and quantifiable metrics. Structure the information hierarchically using proper heading tags (H2, H3) and include relevant schema.org markup for Organization, Person, or Product schemas depending on your entity type. Tools like Schema Pro or WordLift can automate much of this markup generation. Each fact should include a source or date when possible — AI models favor information with clear provenance. The URL should be simple and descriptive (/about, /company, or /entity-name). Keep paragraphs short and factual rather than marketing-heavy. Include contact information, social media handles, and official website URLs. Test your markup using Google's Rich Results Test to ensure proper parsing.
Common Mistakes
Many companies create grounding pages that read like traditional marketing copy, burying facts in flowery language that AI models struggle to parse. Phrases like "leading innovator in the dynamic landscape of cutting-edge solutions" tell AI systems nothing useful about what you actually do. Another frequent error is mixing opinion with fact. Statements like "we provide the best customer service" are subjective claims AI models can't ground, while "we maintain a 4.8/5 customer satisfaction rating based on 2,847 reviews" gives AI systems citable data. Focus your grounding page on verifiable facts that can be independently confirmed, not marketing claims that require interpretation.