AI Visibility Optimization: The Practical Guide to Getting Named by ChatGPT, Gemini and Perplexity

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How should you get mentioned by ChatGPT and other AI assistants?

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What do you want to know or change?

Just see if AI assistants talk about my businessFollow it over time against my competitorsBe mentioned more often, starting now

AI visibility optimization (also called LLM visibility optimization) has moved from experiment to routine because AI answers now sit between buyers and websites. In a study of 900 US adults published in July 2025, Pew Research Center found that Google users clicked a traditional result in 8% of visits when an AI summary appeared, against 15% without one. When fewer people click, being named inside the answer matters more. This guide is the practical overview: what to measure, which lever to pull first, and a 90-day plan. For the step-by-step strategy, see our 7-step GEO strategy.

What is AI visibility optimization?

AI visibility optimization covers every action that raises the probability that an AI assistant mentions, recommends or links to your brand. It has three levels of outcome, from weakest to strongest:

• Mention: the assistant names your brand in its answer.
• Citation: the answer links to one of your pages as a source (see LLM citations).
• Recommendation: your brand appears in the shortlist the assistant suggests for a buying question, ideally near the top.

The discipline has an academic basis. The paper GEO: Generative Engine Optimization (Aggarwal et al., accepted at KDD 2024) showed that changes to the content of a source, such as adding statistics, quotations and cited sources, can boost its visibility in generative answers by up to 40% in their test setting. AI visibility optimization applies that idea beyond the page itself: to your brand, the web around it and the technical access to your site.

How do AI assistants decide which brands to name?

An answer draws on two kinds of knowledge. The first is what the model learned during training, a frozen picture of the web up to a cutoff date: brands that were widely and consistently described before that date are "known". The second is live retrieval: assistants with web search (ChatGPT search, Perplexity, Gemini, Google AI Mode) run their own searches, read a handful of pages and build the answer from them. Google states in its guidance on AI features that a page only needs to be indexed and eligible to be shown with a snippet to appear as a supporting link in AI Overviews or AI Mode, with no extra technical requirement.

The practical consequence: you influence training data slowly (through the reputation and consistency of your brand across the web) and live retrieval quickly (through pages that rank, are readable and answer the exact question). A good plan works on both at once.

What are the six levers of AI visibility?

1. Measure your current AI visibility

Write 25 to 50 questions your buyers ask, across the journey: category discovery ("best invoicing software for freelancers"), use cases, comparisons, alternatives and questions about your own prices and reliability. Run them in each assistant that matters to your market, in a clean session, and note for each answer whether you are named, in which position, which competitors appear and which sources are cited. Our AI visibility audit method details the template, and the free LLM citation checker gives a first reading for a single question. Because answers vary from one run to the next, read rates over many questions, never a single answer.

2. Publish pages the AI can quote

For every question where competitors are named and you are not, you need a page that answers it better. Retrieval systems extract passages, so each section should stand on its own: a question as heading, the direct answer in the first two sentences, then the details, a table when things compare, figures with a named source and a date. Comparison pages, "best X for Y" lists, alternatives pages, pricing explanations and definitions are the formats assistants quote most for buying questions. Our guide on how to optimize content for AI search lists 12 page-level techniques, and the LLM readability checker tests a page in seconds.

3. Make your brand a clear entity

A model can only recommend what it can describe. Use the same brand name, the same one-sentence category description and the same core facts (offer, audience, location, founding year, pricing logic) on your homepage, about page, social profiles, directories and marketplace listings. Add Organization structured data with links to your official profiles. Contradictions (an old tagline on a directory, a discontinued plan on a review site) are a common reason assistants describe a brand wrongly. The glossary entry on entity SEO explains how search systems connect these signals.

4. Earn mentions on the sources AI assistants read

When an assistant answers "which tool should I choose", it leans on pages written by others: comparison articles, review platforms, forums such as Reddit, YouTube videos, trade media and directories. Look at the sources cited in your panel answers: they form your target list. Then get your brand onto those pages through an updated listing, a review campaign among real customers, expert contributions or a data study that journalists can reuse. Our study of the platforms AI assistants cite most shows which types of sites dominate, and the LLM seeding guide covers how to place your brand on them.

5. Keep your site open to AI crawlers

An assistant cannot quote a page its crawler cannot fetch. Each provider uses separate bots for training and for search. OpenAI, for example, documents in its crawler documentation that sites opted out of OAI-SearchBot will not be shown in ChatGPT search answers, while GPTBot concerns training. You can therefore refuse training and still allow search. Check robots.txt, firewall and bot-protection rules (which sometimes block AI crawlers by default) and make sure your main text is in the HTML rather than loaded only by JavaScript. Our guide to robots.txt for AI crawlers lists the user agents to allow.

6. Track and repeat

AI visibility moves with every model update and every new source. Run the same panel on a fixed schedule and follow four numbers: mention rate (share of prompts where you are named), citation rate (share where one of your pages is linked), share of voice against your main competitors, and the accuracy of what is said about you. In Google, AI Overviews and AI Mode traffic is counted in the Web search type of the Search Console Performance report, according to the same Google page; for other assistants, watch referral traffic from their domains in your analytics.

Which lever should you pull first?

The right order depends on what the measurement shows. Use this diagnostic:

What does a 90-day AI visibility plan look like?

1. Days 1 to 15: build the prompt panel, run the baseline, check crawler access and fix any blocking rule.
2. Days 15 to 45: align your entity (homepage, about page, profiles, directories) and publish the first pages for the five questions with the largest gap.
3. Days 45 to 75: work the third-party sources found in the answers: listings, reviews, expert contributions, one data asset.
4. Days 75 to 90: rerun the full panel, compare mention rate and share of voice with the baseline, then reallocate effort to the levers that moved.

How does AI visibility optimization fit with SEO?

The two overlap more than they differ. Assistants that search the web start from search results, so pages that rank on Google and Bing are the pages most likely to be retrieved; Google's own guidance states that no special optimization is needed for its AI features beyond SEO fundamentals. AI visibility optimization adds three layers on top of classic SEO: tracking prompts instead of only keywords, writing in self-contained answer blocks, and working the brand's reputation on third-party sites. Teams that already run SEO well mostly need the measurement and the third-party work. The best AI visibility tools compares the platforms that track prompts at scale.

Sorank is our product: it is an SEO and GEO software that runs these levers on autopilot. It tracks your brand in ChatGPT, Claude and Gemini (plus Perplexity and Grok from the Pro plan) on 25 to 150 prompts, shows who is cited instead of you, and writes and publishes the citable articles that close the gaps with its GEO optimization features. Plans start at $49 per month billed annually, with a 3-day free trial on the pricing page.

The essentials

AI visibility optimization comes down to measuring your presence on real buyer questions, then giving the assistants a clear entity, citable pages, outside proof and open access. Start with the baseline: run a free GEO audit of your site, then build the panel and work the lever your symptoms point to.