AI SEO Glossary

An AI citation occurs when an AI search engine like Perplexity references your website as a source for information in its response. Getting cited by AI is the new "ranking #1" because it means AI trusts your content enough to recommend it to users. **Why AI Citations Matter** AI citations are more valuable than traditional rankings because: - **Higher trust**: Users trust AI recommendations more than search results - **Higher conversion**: AI-referred traffic converts at 23x higher rates - **Better visibility**: Being cited puts your brand in front of users at the decision moment - **Compounding authority**: AI citations reinforce your authority, leading to more citations **Which AI Platforms Show Citations?** | Platform | Shows Citations | Citation Format | |----------|-----------------|-----------------| | Perplexity AI | Always | Numbered footnotes with clickable links | | Google AI Overviews | Usually | "Sources" section below summary | | ChatGPT (with browsing) | When enabled | Inline links in response | | Claude (with web access) | When enabled | Reference links | | Microsoft Copilot | Always | Superscript numbers with sources | **How to Get Cited by AI** 1. **Create authoritative content**: Cover topics comprehensively with original insights 2. **Build domain authority**: Get backlinks from respected publications 3. **Be factually accurate**: AI models verify information across sources 4. **Use clear structure**: Headers, lists, and direct answers make content easier to cite 5. **Keep content fresh**: Recently updated content is preferred 6. **Include citable data**: Statistics, research findings, and unique data get cited **Tracking Your AI Citations** Unlike traditional rankings, AI citations are harder to track because they happen in real-time conversations. Tools like FirstSearch monitor your brand's AI visibility across platforms and alert you when you appear in AI responses. **Citation vs Recommendation** Not all AI mentions are equal: - **Citation**: AI references your content as a source ("According to [your site]...") - **Recommendation**: AI suggests your product/service ("You might want to check out [your brand]...") - **Mention**: AI includes your brand in a list or comparison All three have value, but recommendations typically drive the most conversions.

AI content optimization is the process of structuring and writing content so that AI models can easily understand and extract key information. This includes using clear headings, direct answers, comprehensive coverage, and logical organization that helps AI comprehend your expertise.

AI crawlers are bots used by AI companies to index web content for training or real-time retrieval. Examples include GPTBot (OpenAI), ClaudeBot (Anthropic), and PerplexityBot. Unlike blocking these crawlers, allowing them helps AI models learn about and recommend your business.

AI Overview (formerly SGE - Search Generative Experience) is Google's AI-powered search feature that provides AI-generated summaries at the top of search results. Appearing in AI Overviews requires the same optimization strategies as other AI search: comprehensive, authoritative content.

AI perception describes how AI models understand and characterize your business. It encompasses what AI thinks you do, who your customers are, and whether AI would recommend you. Poor AI perception leads to missed opportunities when potential customers ask AI for recommendations.

AI search refers to search experiences powered by artificial intelligence, where users receive direct answers from AI models rather than a list of links. Examples include ChatGPT, Perplexity, Claude, Google's AI Overviews, and Microsoft Copilot. AI search users convert at 23x the rate of traditional search.

AI SEO (Artificial Intelligence Search Engine Optimization) is the practice of optimizing your online presence to be discovered and recommended by AI-powered search engines and assistants like ChatGPT, Perplexity, Claude, and Google's AI Overviews. Unlike traditional SEO which focuses on ranking in link-based search results, AI SEO focuses on being the answer AI models provide. **Why AI SEO Matters** The shift to AI search represents a fundamental change in how people find information online. Over 100 million people use ChatGPT weekly, and Perplexity is the fastest-growing search product in history. Most importantly, users who get recommendations from AI convert at 23x higher rates than traditional search users because AI recommendations carry implicit trust. **Key Statistics:** - 40% of Gen Z now prefer AI search over Google - AI search users have 23x higher conversion rates - Perplexity processes over 10 million queries daily - Google's AI Overviews appear in 84% of searches **Core AI SEO Strategies:** 1. **Create comprehensive content** that thoroughly covers topics (2,000+ words for pillar content) 2. **Build topical authority** by publishing interconnected content clusters 3. **Ensure consistent brand information** across all online properties 4. **Use clear content structure** with headings, lists, and direct answers 5. **Build quality backlinks** from authoritative sources 6. **Add schema markup** to help AI understand your content **How AI SEO Differs from Traditional SEO:** - Traditional SEO optimizes for keyword rankings; AI SEO optimizes for being the recommended answer - Traditional SEO focuses on click-through rates; AI SEO focuses on citations and mentions - Traditional SEO targets Google's algorithm; AI SEO targets LLM comprehension - Both benefit from quality content and strong E-E-A-T signals

AI visibility refers to how well AI assistants understand and can accurately describe your business. High AI visibility means ChatGPT, Perplexity, and other AI tools can correctly identify what you do, who you serve, and why you're a good choice—leading to more recommendations.

Answer Engine Optimization (AEO) is the practice of optimizing content to be the direct answer to user questions. With AI search providing direct answers rather than links, AEO has become essential. It involves structuring content to clearly and concisely answer common questions.

A backlink network in AI SEO refers to a system of interconnected websites that link to each other to build domain authority. Strong backlink profiles signal trustworthiness to both traditional search engines and AI models, increasing the likelihood of being cited or recommended.

ChatGPT SEO is the practice of optimizing your business to be mentioned and recommended by ChatGPT when users ask questions related to your industry. This involves creating comprehensive content, building topical authority, and ensuring consistent brand information across the web.

Content authority refers to how trustworthy and expert your content appears to search engines and AI models. It's built through comprehensive coverage, accurate information, citations from other authoritative sources, and consistent publishing in your area of expertise.

E-E-A-T stands for Experience, Expertise, Authoritativeness, and Trustworthiness. Google uses E-E-A-T to evaluate content quality, and AI models similarly assess sources before citing them. Demonstrating E-E-A-T through author bios, credentials, and quality content improves both traditional rankings and AI visibility. **The Four Components of E-E-A-T** **Experience** (added in 2022): First-hand experience with the topic. Google values content from people who have actually used products, visited places, or done the work themselves. **Expertise**: Demonstrated knowledge and skill in the subject matter. For YMYL topics (health, finance, legal), formal credentials matter more. **Authoritativeness**: Recognition from others in your field. Backlinks, mentions, and citations from authoritative sources signal authority. **Trustworthiness**: The foundation of E-E-A-T. Content must be accurate, transparent about sources, and published on a secure, well-maintained website. **Why E-E-A-T Matters for AI SEO** AI models evaluate similar trust signals when deciding which sources to cite: - They prefer content from recognized experts - They weight sources by domain authority - They verify claims against multiple sources - They favor fresh, well-maintained content **How to Demonstrate E-E-A-T:** | Signal | How to Implement | |--------|------------------| | Author bios | Add detailed bios with credentials, experience, and links to other work | | About page | Explain who you are, your mission, and your expertise | | Citations | Link to authoritative sources when making claims | | Backlinks | Earn links from respected publications in your field | | Reviews | Gather authentic customer reviews and testimonials | | Contact info | Display clear contact information and physical address (if applicable) | | HTTPS | Use SSL certificate for secure browsing | | Content accuracy | Fact-check everything; update outdated information | **E-E-A-T for Different Content Types:** - **Product reviews**: Show you've actually used the product (photos, specific details) - **How-to guides**: Demonstrate you've successfully done what you're teaching - **Health/finance**: Include credentials of medical/financial professionals - **Local business**: Display NAP, licenses, certifications, local reviews **Common E-E-A-T Mistakes:** - Generic "admin" or company-only author bylines - No author bios or credentials - Missing contact information - Outdated content with old statistics - No external citations or sources

Entity recognition in AI SEO refers to how AI models identify and categorize your brand as a known entity. When AI recognizes your business as an entity associated with specific topics, it's more likely to mention you in relevant queries. Consistent NAP (Name, Address, Phone) and schema markup help with entity recognition.

A featured snippet is a highlighted search result that appears at the top of Google's search results, providing a direct answer to a user's query. Content that wins featured snippets is often the same content AI models cite, as both prioritize clear, direct answers.

GEO stands for Generative Engine Optimization, a term coined to describe SEO strategies specifically designed for generative AI search engines. GEO focuses on optimizing content so that large language models can understand, trust, and cite your information when generating responses to user queries. **The Origin of GEO** The term "Generative Engine Optimization" emerged in 2024 as AI search became mainstream. It describes the specific strategies needed to appear in AI-generated responses rather than traditional search result pages. GEO, AI SEO, and LLM SEO are used interchangeably by practitioners. **How GEO Works** Unlike traditional SEO where algorithms evaluate pages based on keywords and links, generative engines synthesize information from multiple sources to create answers. Your content needs to be: 1. **Comprehensive enough** to be a primary source on the topic 2. **Structured clearly** so AI can extract key information 3. **Factually accurate** with verifiable claims 4. **Consistently published** to build topical authority **GEO Best Practices:** - Write content that directly answers questions (Q&A format helps) - Include statistics and data points that AI can cite - Use clear headings that describe section content - Create content clusters around your expertise areas - Build backlinks from authoritative sources - Keep content fresh and regularly updated **Example of GEO in Action:** When a user asks ChatGPT "What is the best project management tool for small teams?", the AI synthesizes information from dozens of sources. GEO-optimized content that comprehensively covers this topic, includes comparison data, and comes from an authoritative domain is more likely to influence the AI's response. **GEO vs Traditional SEO:** Traditional SEO aims to rank #1 for a keyword. GEO aims to be one of the 3-5 sources AI trusts enough to cite. Both can coexist in your content strategy.

A knowledge graph is a database of interconnected entities and their relationships. Google's Knowledge Graph powers many search features, and AI models build similar understanding of entities. Being recognized in knowledge graphs increases your chances of AI recommendations.

LLM SEO (Large Language Model SEO) refers to optimization strategies targeting large language models like GPT-4, Claude, and Gemini. The goal is to ensure these AI models understand your business and recommend it when users ask relevant questions. LLM SEO is synonymous with AI SEO and GEO.

Perplexity SEO focuses on getting your content cited by Perplexity AI, a search engine that provides answers with sources. Since Perplexity browses the web in real-time and always shows citations, domain authority and fresh, cite-worthy content are crucial for Perplexity SEO.

Schema markup is structured data added to web pages that helps search engines understand content. It can identify businesses, products, FAQs, articles, and more. Schema markup helps both traditional search and AI models accurately understand and categorize your content.

Semantic SEO focuses on meaning and context rather than exact keyword matches. It involves creating content that comprehensively covers topics and their related concepts. AI models excel at understanding semantics, making semantic SEO crucial for AI visibility.

Topical authority is the perceived expertise a website has on a particular subject. AI models trust sources that demonstrate comprehensive knowledge of their field. Building topical authority involves creating interconnected content that thoroughly covers all aspects of your expertise area.

Traditional SEO focuses on optimizing websites to rank in conventional search engine results pages (SERPs) like Google. It emphasizes keywords, backlinks, technical optimization, and content quality to achieve higher rankings in link-based search results.

Zero-click searches are queries where users get their answer directly on the search results page without clicking through to a website. AI search is essentially all zero-click—users get answers from AI without visiting sites. The goal shifts from getting clicks to being the cited source.