Guides
Practical guides to AI visibility, GEO, and getting cited by ChatGPT, Perplexity & co.
What is GEO (Generative Engine Optimization)?
GEO (Generative Engine Optimization) is the practice of getting your brand mentioned, cited and recommended inside AI answers — ChatGPT, Perplexity, Gemini, Claude, Copilot and Google AI Overviews — the way SEO got you ranked on Google.
Read →How to check if ChatGPT (and other AIs) mention your brand
To check if ChatGPT mentions your brand, ask the engines the questions your buyers actually ask, then record whether you're named, your position, the sentiment, and the sources cited — across ChatGPT, Perplexity, Gemini, Claude, Copilot and Google AI Overviews. A tool like CitePeak does this in seconds.
Read →The AI Visibility Score, explained
The AI Visibility Score is a single 0–100 number for how visible your brand is across AI answer engines. CitePeak computes it from five weighted dimensions: Coverage (0.30), Prominence (0.25), Share of Voice (0.20), Citations (0.15) and Sentiment (0.10).
Read →GEO vs. traditional SEO: what each optimizes for, where they overlap, and why you need both
Traditional SEO optimizes for ranked links on a results page; GEO optimizes for being mentioned and cited inside AI answers from ChatGPT, Perplexity or Google AI Overviews. They share content quality and authority, but GEO measures whether the model names you, not whether you rank.
Read →How to Get AI Engines to Mention Your Brand: A Prioritized Checklist
Prioritized order: (1) answer-first content and FAQs, (2) consistent entity and brand info, (3) earn citations from trusted sources, (4) structured data, (5) measure over time. Do the high-leverage content work first, then build authority and track results.
Read →Why Your Brand Doesn't Show Up in AI Answers: A Diagnostic Guide
If AI engines like ChatGPT or Perplexity skip your brand, the cause is usually one of five things: thin content, weak entity presence, no trusted citations, a low-authority domain, or an ambiguous name. Diagnose the gap first, then fix the highest-impact one.
Read →How AI Answer Engines Choose and Cite Sources (Honestly Explained)
AI answer engines pull from two layers: their training data (a frozen snapshot of the past) and live retrieval that grounds answers in fresh web sources. They quote passages that are clear, factual, well-structured, and authoritative, then cite the URLs they actually used.
Read →llms.txt Explained: What It Is and Whether Your Business Needs One
llms.txt is a proposed plain-text file at your site root that points AI models to your most important content in clean Markdown. It is a community draft, not an official standard, and major AI engines have not confirmed they read it. Low effort, uncertain payoff.
Read →Structured Data & Schema.org for AI Visibility: What Actually Helps
Schema.org markup translates your page into a machine-readable format so AI engines parse facts unambiguously. It does not force citations, but clean Organization, FAQPage, Article and Product data removes guesswork and reduces the chance an AI misstates your brand.
Read →How to get ChatGPT to mention and cite your brand
To get ChatGPT to mention and cite your brand, publish clear answer-first content, earn references on the third-party sources ChatGPT draws from, and keep your entity facts consistent everywhere. There are no guarantees — but these moves stack the odds in your favor.
Read →How to Appear in Google AI Overviews: What Helps vs What Is Myth
To show up in Google AI Overviews, build a solid conventional SEO base, answer the exact query directly and early, add clean structured data, and earn trust as a credible source. AI Overviews mostly draw from pages that already rank well, so SEO fundamentals still carry most of the weight.
Read →AEO vs GEO: What the Terms Mean and Why the Work Is the Same
AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) are near-identical labels: both aim to make your brand the cited, quotable answer in AI tools like ChatGPT and Perplexity. The terms differ mostly in framing, not in the practical work you actually do.
Read →AI Visibility for B2B SaaS: A Practical Playbook
For B2B SaaS, AI visibility means showing up when buyers ask AI engines for the best, alternatives, and comparisons in your category. Win the review sites, listicles, and communities those answers cite, then track your mention rate across engines over time.
Read →How to Measure Your AI Share of Voice vs Competitors
AI share of voice is the percentage of buyer-intent prompts where your brand gets named or cited across engines, relative to rivals. Measure it with a fixed prompt set, run the same prompts on each engine, and read the trend over weeks, not one snapshot.
Read →How to Earn Presence on the Sources AI Engines Cite Most (Reddit, G2, Wikipedia, YouTube, Listicles)
AI engines often cite third-party sources like Reddit, G2/Capterra, Wikipedia, YouTube, and industry listicles instead of your own site. Earning honest presence there - through real reviews, genuine community contributions, and getting included in roundups - is one of the most reliable ways to grow AI visibility.
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