How to Get Your Brand Cited by ChatGPT, Gemini & Perplexity

GEO is the practice of optimizing your brand to be cited in AI-generated answers, not just ranked in search results. When someone asks ChatGPT "what is the best CRM for a 10-person sales team?" or Perplexity "what agency should I hire for AI automation?", GEO determines whether your brand shows up in the response.

The core difference from SEO: in traditional search, you can rank sixth and still get traffic. In AI chat interfaces, you are either cited or you are not. There is no page two.

The term was formally defined by researchers from Princeton, Georgia Tech, The Allen Institute for AI, and IIT Delhi in a paper presented at ACM SIGKDD 2024. Their key finding: the right content optimizations can increase AI visibility by up to 40%, and these gains do not correlate with traditional SEO rankings.

The standard pitch for GEO is volume: AI search is growing fast. That is true. ChatGPT processes 2.5 billion requests per day; Perplexity tripled its query volume in under twelve months; AI Overviews now appear in at least 16% of all Google searches.

But the more compelling argument is conversion quality. AI-referred traffic converts at 14.2% versus 2.8% from standard Google search. Visitors from AI sources spend 68% more time on websites. Webflow reports that LLM-sourced visitors convert at 6x the rate of Google Search visitors.

Why the difference? Someone using an AI assistant for research has already committed to finding a solution. They are further along in the decision process than a keyword searcher. When ChatGPT names your product specifically, it functions like a personal recommendation from a trusted source.

Companies that have started tracking this: SmartRent reported 32% of sales-qualified leads originating from ChatGPT citations within six weeks of optimizing for AI visibility. Broworks saw 27% of their AI-referred traffic convert to Sales-Qualified Leads within 90 days.

LLMs use a two-layer process when generating responses about brands or products.

The first layer is parametric memory: knowledge embedded in the model's weights during training. Every LLM was trained on massive text datasets (The Pile, RefinedWeb, Common Crawl) scraped from the web up to a cutoff date. Brands that appeared consistently in that data, especially in reviews, comparisons, news coverage, and documentation, have a baseline presence in the model's understanding of the world. Brands not in the training data have zero baseline recognition, regardless of how good their product is.

The second layer is real-time retrieval (RAG). Modern AI assistants like ChatGPT with Browse, Perplexity, and Google AI Overviews can query live web sources before generating a response. According to Evertune research, 62% of ChatGPT responses use parametric memory only, while 38% trigger live retrieval. When retrieval is triggered, content recency and structured markup become primary signals.

Brands present in both training data and optimized for RAG retrieval achieve 4.7x higher citation rates than brands relying on only one mechanism, per Semrush's 2025 AI Visibility Study.

The practical implication: if you are a newer brand or in a competitive category, you cannot wait for the next training data update. You need to optimize for real-time retrieval now.

The Princeton study tested multiple content optimization tactics across 10,000 queries and ranked them by visibility impact. The three highest-performing strategies were: cite sources, add statistics, and add quotations. Traditional keyword tactics ranked near the bottom.

Here is what to prioritize:

1. Earn third-party mentions. Your own website represents only 5 to 10% of the sources AI systems draw from. The other 90 to 95% is reviews (G2, Capterra, Trustpilot), news coverage, comparison articles, forum discussions (Reddit is heavily cited by LLMs), and podcast mentions. Brands in the top 25% for web mentions receive 10x more AI visibility than others. This is the highest-leverage GEO activity.

2. Structure content to answer questions directly. AI systems favor content where the direct answer appears before the explanation. Write for how users phrase questions to AI assistants, not for keyword density. Clear H2 and H3 hierarchy, numbered lists, comparison tables, and explicit FAQ sections all help AI parse and reuse your content.

3. Cite external sources in your own content. This was the single most effective tactic in the Princeton study, producing a 30 to 40% visibility increase. When your articles explicitly name and cite trusted external sources in body text, not just as hyperlinks, AI systems treat your content as more authoritative and more usable.

4. Add statistics, data, and named quotes. "Statistics addition" and "quotation addition" ranked second and third in the Princeton study. Specific benchmarks, original research, named expert quotes, and charts are highly citable. Vague or promotional language is ignored by AI.

5. Implement schema markup. Pages with proper schema are 3x more likely to earn AI citations. FAQPage schema alone produces a 3.2x citation rate increase and AI-referred sessions jumped 527% on FAQ-marked pages in 2025. Product, Organization, and Service schema round out the priority list.

6. Build entity authority. Wikipedia is in the training data of every major LLM. Google's Knowledge Graph contains 500 billion facts about 5 billion entities. Entities with robust Knowledge Graph presence achieve 89% higher citation rates in AI responses. Ensure consistent sameAs links in your schema, claim your Google Knowledge Panel, and add Person schema for authors and team members.

Schema markup is the most actionable technical change for GEO because the data is clear and the implementation is specific.

Only 12.4% of websites currently implement structured data, which makes it a significant competitive advantage for anyone who does. GPT-4's performance on comprehension tasks improves from 16% to 54% when given structured versus unstructured content.

The priority schema types, ranked by citation impact:

FAQPage: the highest citation lift of any schema type. Pages using FAQPage schema are 3.2x more likely to appear in AI Overviews and earned AI-referred sessions increased 527% in 2025. If you have a FAQ section on any page, adding FAQPage schema is a one-hour implementation with measurable results.

Organization/Brand: a site-wide identity signal. Include your name, logo, founding date, contact details, social profiles, and sameAs links to LinkedIn, Crunchbase, and your Wikipedia page if one exists. This helps AI systems build an accurate entity model of your company.

Article/BlogPosting: signals freshness, authorship, and E-E-A-T. Include author name with Person schema, published date, and modified date. This is especially important for content that could become outdated.

Service and HowTo: important for service businesses. Service schema with areaServed, provider, and description helps AI answer category queries that include location or service type.

Most companies have no idea whether AI systems mention them at all. Only 16% of brands today systematically track AI search performance.

The manual method is free and takes 30 minutes a month: ask ChatGPT, Perplexity, and Gemini the questions your customers would ask. Document whether your brand appears, how it is described, and what competitors are mentioned alongside you. Run the same queries monthly and track changes.

For teams that want systematic tracking, the main tools as of early 2026:

Otterly AI ($29/month): tracks mentions across 6 platforms including ChatGPT and Gemini. Best for smaller teams and agencies.

Ahrefs Brand Radar: included in existing Ahrefs plans, tracks ChatGPT, AI Overviews, and Perplexity. Good if you are already on Ahrefs.

Profound ($499/month): enterprise tool built for Fortune 500 brands tracking at scale across ChatGPT, Perplexity, Gemini, and Copilot.

Beyond the dedicated tools: set up GA4 to track referral traffic from chat.openai.com, perplexity.ai, gemini.google.com, and claude.ai. AI visitors who arrive via citations have distinct behavioral patterns (high time on page, low bounce, higher conversion).

Spain accounts for 3.7% of global ChatGPT traffic, on par with the UK and ahead of Germany. Mexico adds another 4.1%, and the full Spanish-speaking world represents approximately 12 to 13% of global ChatGPT usage.

Nearly all GEO content, strategies, and optimized brand presences are in English. Spanish-language companies that act on GEO now compete in a market with significantly less noise.

What this means practically: Spanish-language FAQPage schema, Spanish-language service descriptions, and citations in publications like El País, Expansión, América Economía, and Cinco Días will compound into AI authority faster than equivalent efforts in English-language markets where competition is already established.

The Hispanic B2B market is also a strong match for AI search behavior: Perplexity's audience skews 80% graduates and 30% senior company leaders, which aligns with the decision-makers a B2B agency needs to reach.

A sensible starting point is an audit before any changes. Run 20 to 30 queries in ChatGPT and Perplexity that reflect how your customers search for solutions. Note which competitors appear and how they are described. That baseline tells you where the gap is.

From there, the highest-ROI actions:

First week: add FAQPage schema to your service pages. This is a one-hour implementation and the data on citation lift is consistent across studies.

First month: review your content for direct answers. For every major service or product page, make sure the clearest description of what you do appears in the first paragraph, not buried three sections down.

Ongoing: build a citation pipeline. Identify 10 to 15 publications and review sites where your category is covered. Pitch for inclusion. Getting one solid piece of third-party coverage per month compounds quickly, because each mention increases your probability of appearing in AI responses that cite that source.