How to Analyze Visibility in ChatGPT and Other LLMs in 2026

To check your brand’s visibility in AI systems, collect 30–50 queries your audience actually uses, run them through ChatGPT, Gemini, and Perplexity, and record how many answers mention you and your competitors. At the same time, check robots.txt to make sure AI crawlers can access the site and create a GA4 segment for referral traffic from chatgpt.com, perplexity.ai, and other AI platforms.

o check your brand’s visibility in AI systems, collect 30–50 queries your audience actually uses, run them through ChatGPT, Gemini, and Perplexity, and record how many answers mention you and your competitors. At the same time, check robots.txt to make sure AI crawlers can access the site and create a GA4 segment for referral traffic from chatgpt.com, perplexity.ai, and other AI platforms.

AI Visibility is a brand’s presence in answers generated by systems such as ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews, and other LLMs.

The same area of work goes by different names. GEO stands for Generative Engine Optimization. AEO stands for Answer Engine Optimization. You will also see terms such as LLM visibility and AI Search Visibility. The differences are more about marketing terminology than substance.

The key difference from traditional search is that the model does not show ten links. It gives one answer. You are either included in that answer, or for that user you effectively do not exist. There is no “we rank eighth” here.

The second difference is that the same model can answer the same query differently. The wording, language, conversation history, enabled web search, region, and context all affect the result. That is why a single check proves nothing.

When analyzing AI Visibility, it is not enough to look only at whether the brand was mentioned. You need to understand how often it appears, which competitors appear alongside it, the context in which it is mentioned, which sources the model cites, and whether users actually click through to the site from AI systems.

Two metrics do most of the work. Share of Voice shows the gap between you and the market. Without it, mention frequency says very little: 6 mentions out of 40 looks poor until you discover that the leader has only 8.

Source citations show where to focus. If the model consistently cites three industry directories in your niche, the job is to get into those directories, not simply publish another page on your own site.

Paid tools become useful when you have many prompts, competitors, languages, countries, and recurring measurements. But you can start without a budget using a prompt spreadsheet, GA4, server logs, and Search Console.

Google Analytics 4

AI systems can send referral traffic. In GA4, create an exploration by source and separately check visits from platforms such as:

• ✓chatgpt.com
• ✓perplexity.ai
• ✓gemini.google.com
• ✓copilot.microsoft.com
• ✓claude.ai

GA4 only shows users who actually clicked through to the site, and most people do not. Still, these pages are already attracting visitors from AI systems, so they should be analyzed and strengthened first.

Server Logs

Server logs show which crawlers actually visit the site. This matters because if AI bots cannot access your pages, content improvements will not produce the expected result.

User agents worth looking for:

GPTBot, OAI-SearchBot, ChatGPT-User — OpenAI

ClaudeBot, Claude-User — Anthropic

PerplexityBot — Perplexity

Google-Extended — Google

CCBot — Common Crawl

If the bots are missing or important pages are blocked in robots.txt, solve the access problem first. Only after that does it make sense to work on content, external mentions, and citations.

Search Console

Google Search Console does not provide a separate report for AI Overviews. It is still useful for indirect analysis.

One signal is pages where impressions remain stable while CTR declines. These are often queries where a generated answer has appeared and absorbed some of the clicks.

Search Console also helps you see which pages already have organic demand, which queries are growing, which content should be updated, and which pages can become a foundation for GEO optimization.

Manual checking works at the beginning. After a certain scale, however, it runs into three problems.

Before comparing tools, it is important to understand one technical detail: services can collect data in different ways, so their numbers will not always match.

Some tools query a model directly through its API. This is fast, cheaper, and reproducible. But an API response may differ from what a user sees in the real interface because the model version, web search settings, or system instructions may be different.

Other tools emulate the real interface, including web search, region, a clean session, and conditions closer to actual user behavior. This is more expensive to operate, so these services often impose stricter prompt limits.

As a result, one service may show a Share of Voice of 12% and another 4%, and both can be correct within their own methodology. Compare trends within the same tool. Absolute values from different platforms should not be compared directly.

Pricing is current as of July 28, 2026. Before paying, check current prices, limits, and supported AI systems on the service’s website.

Support for Ukraine and the Ukrainian language should be checked separately for each service and plan. Not every platform publishes a complete list of locales, and some count each language or country as a separate prompt allowance. Before paying, verify three things: whether Ukraine can be selected as a location, whether Ukrainian-language prompts are processed correctly, and whether adding a second language doubles the cost. The most reliable option is to launch a trial project using real Ukrainian queries.

Ahrefs Brand Radar makes sense for teams that already use Ahrefs in their SEO processes. Its main value is not only the AI module itself, but also the fact that backlinks, organic keywords, and competitor data are available in the same interface.

For example, if the model cites someone else’s directory, you can immediately inspect its backlink profile and decide whether getting listed there is realistic. A standalone GEO service does not always provide that context.

The entry price is high, and checks above the included limit are sold in additional packages. If you already use Ahrefs, Brand Radar is worth testing. Buying Ahrefs only for this module is not always rational because the same budget can buy deeper GEO analysis in a specialized service.

Semrush AI Visibility Toolkit is a logical choice for teams that already work in Semrush. The module sits inside a familiar interface, the data fits into existing reports, and the team does not need to learn a new platform.

The service works well for basic domain visibility analysis, competitor research, and prompt discovery. It is convenient when you want to add AI Visibility to an existing SEO workflow quickly.

The main drawback for agencies is per-domain pricing. Ten clients means ten separate payments. The analysis of the answers themselves is also less detailed than in specialized services: you can see that you were mentioned, but not always exactly what the model says about you or why.

Amplitude should be treated carefully in a list of GEO tools. It does not check whether ChatGPT mentions you and is not a direct AI Visibility monitoring tool. It is a product analytics platform.

Its role starts after the user has already reached your site. Amplitude helps you understand how AI traffic behaves, whether visitors reach the target action, whether they sign up or buy, and how much revenue they generate.

The tool is useful when you need to prove to management that AI traffic converts. But it does not answer why a brand is missing from ChatGPT or Perplexity. For that, you need a separate GEO tool.

Profound analyzes not only whether a brand is mentioned, but also the content of the answer: the context in which the brand appears, which claims the model repeats, where those claims came from, and how competitors are described alongside you.

This is important for reputation work. If a model consistently says something inaccurate, outdated, or undesirable about a brand, Profound can help identify the sources behind that information. You can then work with the sources, content, and external mentions.

The tool is aimed more at mid-size and large brands. For a small project, it may be too expensive or too complex at the beginning.

Peec AI is one of the most balanced options for a team focused specifically on GEO.

The logic is simple: you create a prompt set, the service runs it regularly, shows your visibility share against competitors, and analyzes which URLs the model cites as sources. The last part is especially useful because it often turns directly into link-building and content tasks.

The plans let you scale gradually. Starter is enough to test a hypothesis, while Pro supports full monitoring. The prompt allowance on the entry plan is limited, however, so you may outgrow it quickly.

The product is young and changes frequently. For some teams that is a drawback; for others it is an advantage because the service responds quickly to new market needs.

OtterlyAI is one of the cheapest ways to find out whether you have an AI Visibility problem at all.

The Lite plan can work for an initial snapshot: a handful of prompts, several AI systems, and minimal reporting. That is enough for the first month. You either discover that competitors are visible while you are not, or you find that models barely answer questions about your niche yet.

For long-term monitoring, you will need to move to a higher plan. At that point, the price becomes closer to specialized solutions while the feature set may still be weaker. That makes OtterlyAI a reasonable entry point rather than an obvious primary platform for an entire year.

For an agency with a portfolio of clients, the service can become inconvenient because of limits and scaling.

KIME is suitable for teams that want transparent pricing and regular brand monitoring across AI systems.

Explorer at €99 includes 50 prompts, two AI systems, and one user. Core at €399 opens broader capabilities for a team and recurring analysis.

The main advantage is that it is clear what you are paying for. The main drawback is that a team with several users and wider coverage needs to budget for Core immediately. That can be too high a starting point for a small project.

The AI Visibility market is evolving quickly, so beyond the main services it is worth watching other platforms as well.

• ✓Scrunch AI — brand presence monitoring with an enterprise focus.
• ✓Evertune — analysis of how models perceive a brand at the training-data level.
• ✓Rankscale — tracking rankings and mentions in generative search.
• ✓Goodie AI — a platform for managing brand presence in AI.
• ✓AthenaHQ — competitive benchmarking.
• ✓Brandlight — reputation monitoring.
• ✓SE Ranking AI Visibility — a module inside an SEO platform.
• ✓Serpstat — AI insights layered on top of traditional SEO functionality.

These services do not necessarily belong in the main comparison table, but they are worth knowing. Some may fit a specific task better: enterprise monitoring, reputation management, competitor comparison, or working inside an SEO platform your team already knows.

The money-saving order is simple: first build your prompt set manually and run two measurements. A subscription purchased before you know what you actually need to measure can sit unused for the first month.

Before working on content, make sure the site is actually accessible to AI systems. The order matters, and teams often get it wrong.

Brand visibility in AI-generated answers depends on technical access, rendering, content structure, external mentions, source authority, and how easily a self-contained answer can be extracted from your page.

Crawler Access

robots.txt can apply to different types of bots, and blocking one does not mean blocking another.

The main groups are:

• ✓training bots: GPTBot, CCBot, Google-Extended;
• ✓search bots: OAI-SearchBot, PerplexityBot;
• ✓user-triggered bots: ChatGPT-User, Claude-User, which visit a page when a user makes a request.

A common mistake is to block Google-Extended to prevent content from being used for training while still expecting visibility in AI Overviews. Before changing anything, understand exactly which access you are blocking and why.

Example configuration for a site that wants to remain visible to AI systems:

User-agent: GPTBot
Allow: /

User-agent: OAI-SearchBot
Allow: /

User-agent: ChatGPT-User
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent: ClaudeBot
Allow: /

User-agent: Google-Extended
Allow: /

Sitemap: https://example.com/sitemap.xml

This is not a universal template. The rules may differ for media sites, SaaS, legal websites, eCommerce, or YMYL niches. Before making changes, check which pages should remain accessible and which are better blocked.

llms.txt

llms.txt is an experimental format: a simple list of key pages with explanations, intended for models. Not every system supports it, so it should not be the foundation of your entire GEO strategy. Still, the file is quick to create and can be useful as an additional layer of structure.

Example llms.txt for an eCommerce site:

# ROZETKA
> Online store for electronics, appliances, and home products.

## Categories
- [Smartphones](https://rozetka.com.ua/ua/mobile-phones/c80003/preset=smartfon/): smartphones from different brands and price segments
- [Laptops](https://rozetka.com.ua/ua/notebooks/c80004/): laptops for work, study, and gaming
- [TVs](https://rozetka.com.ua/ua/all-tv/c80037/): TVs and Smart TVs

## Help
- [Delivery](https://help.rozetka.com.ua/p/97-dostavka/): delivery terms and options

There is no need to duplicate sitemap.xml in llms.txt. Add only the pages that genuinely explain your products or services, expertise, key resources, and topical clusters.

Rendering

AI crawlers may process JavaScript less reliably than Googlebot. Text that is loaded only on the client side may simply not exist for them.

The check takes only a few minutes: open the page with JavaScript disabled or inspect the raw HTML source. If the main text, tables, FAQ, pricing, or important links are missing there, a large portion of the content may be invisible to the model.

The solution is server-side rendering, prerendering, or moving critical blocks into the HTML.

Structured Data

Schema tells systems explicitly what is on the page: an organization, service, article, product, question, or answer.

For traditional search, this can help with snippets. For models, it also creates an additional machine-readable layer that reduces the risk of misunderstanding the page.

A minimum set for an article about AI Visibility:

• ✓Article;
• ✓FAQPage;
• ✓BreadcrumbList;
• ✓ItemList for the list of tools.

For a service page, it also makes sense to use Service or ProfessionalService.

Text Format

Models extract information more effectively from text built in a certain way:

• ✓a direct answer in the first 40–60 words after the heading;
• ✓tables and numbered lists instead of uninterrupted paragraphs;
• ✓one idea per block;
• ✓specifics: dates, numbers, names, and sources;
• ✓minimal filler at the beginning of a section.

If you cannot extract a self-contained paragraph with a complete answer from your section, the model is unlikely to extract it correctly either.

A model builds its understanding of a brand not only from the brand’s own website. Often, the main sources are everything else: industry media, directories, comparison articles, communities, and reviews.

That is why GEO is not limited to on-site changes. If your niche has “top 10 agencies” lists and you are absent from them, the model has little external evidence that your brand should be recommended. You can publish ten more pages on your own site, but that does not replace presence in third-party sources.

In practice, this means working on external mentions: industry roundups, directories, comparisons, and expert comments in relevant media. Link building matters here, but not only in the traditional backlink sense. For AI Visibility, context matters: which brands you are mentioned alongside, the topic of the mention, the platform where it appears, and whether the mention supports your expertise.

A GEO audit at One2.agency consists of four steps.

A two-week GEO audit helps you understand how ChatGPT, Gemini, Perplexity, and Google AI Overviews see your brand.

The basic check includes:

• ✓30–50 prompts;
• ✓analysis of brand and competitor mentions;
• ✓review of cited sources;
• ✓technical crawler-access check;
• ✓assessment of content readiness for citation;
• ✓a report with current visibility, the gap to competitors, and a three-month action plan.