In 2025, ChatGPT, Gemini, Claude, and other large language models (LLMs) are increasingly becoming the primary source of information for millions of users. For example, ChatGPT already has over 500 million active weekly users, and the share of users starting their search not on Google, but from AI-generated results, keeps growing. In this new information landscape, it’s no longer enough to be “indexed” — it’s essential to be “included in the answer”.
This means that website promotion strategies must take into account not only Google but also the algorithms of generative AI. So if your content isn’t recommended by ChatGPT or other language models, users might never see you.
How ChatGPT and other language models “choose” whom to cite
Language models with internet access can “search” online, but they have their own way of deciding what’s important to the user. So how does generative AI select sources?
Before finding a source, the model reframes the user’s question. It doesn’t just copy the user’s query — it “reinterprets” it. It identifies key concepts, clarifies the context, and creates a search query focused on results. Then, it retrieves a list of web pages — potential sources for information and citation.
Example, your query: “What is a PBN and how does it work?”
AI’s search query: “private blog network definition risks benefits seo impact site
.com OR site
.com OR site
.com OR site
.com”, OR is used to indicate multiple options. AI pre-analyzes sites “on the fly”, evaluating their relevance, authority, and structure — and may even take into account previous interactions with these sources.
So the AI (or the search agent it uses) doesn’t just search for “what is a PBN”, but says to the search engine’s API: “Find me info about PBNs, but preferably from these sites”. The goal is to find the most relevant and authoritative results with the freshest data.
AI makes a request via the API to a search engine (usually Bing or Google) and receives a list of dozens of URLs, each with a short description and title. But this is not yet an answer — only the basis for it.
The neural network analyzes each link and evaluates it against a set of criteria.
Content relevance:
- how accurately the page answers the user’s question
- whether it contains the specific data the user is looking for
Structure and clarity:
- AI prefers information that is easy to “understand”
- clear headings, lists, and tables attract more AI attention
- pages with well-organized data are more likely to be cited
Technical accessibility:
- how easily AI can “read” the page
- sites with clean HTML have an advantage over those overloaded with JavaScript
- content protected from scraping may be skipped by the neural network
Next comes analysis and selection. The AI quickly “reads” the found materials, assesses their relevance to the query, selects fragments that best answer the question, and merges information from different sources into one response.
AI doesn’t copy — it reconstructs the essence based on what it has “read”, and in the final stage, it uses the best sources as citations or confirmations of its “own” words. The format may vary: direct URL reference in brackets [ ], hyperlink in the text.
How to “make” ChatGPT link to your site
Generative AI doesn’t read like a human — it looks for clear, logical, structured blocks of information. Your goal is to make content easy to identify and cite, because machines — unlike people — are uncompromisingly literal. They need structure:
- use H1, H2, H3 headers
- add clear Q&A blocks
- format lists, definitions, tables
Content in FAQ, guide, or checklist format is especially “appetizing” to neural networks.
Write for niches
ChatGPT searches for unique sources, especially in narrow topics:
- original research, local news
- statistics, raw data
- niche analytics not used by large media
Focus on areas where you are the only or best source. Write about local or industry-specific events (e.g., working strategies in a particular sector).
AI prefers fresh data, so if you publish information first and your webpage is well structured — AI will remember you as the original source.
Optimize your site for search engine crawlers
ChatGPT doesn’t index the internet on its own. It “sees” only what Bing or Google see. This means you should:
- ensure indexing
- not block pages in robots.txt
- check your sitemap
- avoid heavy JavaScript rendering in your content
Give AI literal “access” to your site. Pages hidden behind logins, excessive JavaScript, or aggressive ads are often ignored. AI reads fast — if access is complicated, it moves on.
Use structured data (schema.org)
ChatGPT often looks for quick answers — and schema provides a direct path. Markups like Article, FAQPage, HowTo, Breadcrumb help neural networks understand the content type and extract the most relevant info.
AI doesn’t just “grab” text, it chooses what to cite. Create more opportunities for direct mentions:
- include your brand name in the text
- add phrases like “At mysite.com we found…”
- phrase content as complete thoughts — this helps AI filter them
- write in FAQ style — AI loves it for pulling ready-made answers
Like Google, AI models rely on trust signals. So build digital reputation and enrich content with authorship and links:
- work on your backlink profile
- add author info
- build social media presence
The more authoritative sources link to you, the more likely AI will cite you too.
To increase your chances of being quoted by AI, create structured, expert-level, factual content with proper schema markup. Also focus on site authority and quality backlinks.
How to check if GPT already mentions you
With models like ChatGPT, Perplexity, or Copilot gaining web access, a new challenge has emerged for SEO experts: how to know if AI systems use content from your site — and whether that can be turned into a brand opportunity. Yes, it’s possible. One effective method is using technical markers, unique URLs, and watermarks in your content.
Why is this useful? If a user asks ChatGPT for “the best SEO strategies for 2025,” the answer might be based on your site’s data — but you’ll never know unless you track it (unless the AI provides a direct link).
“AI detectors” as a digital bait strategy
One effective method is creating special “baits” for neural networks. This helps detect when your content is used in AI responses.
Unique URL Markers
This technique is similar to UTM tags used to analyze advertising campaigns. Create special URLs designated exclusively for AI:
- Create a dedicated page with a unique identifier, e.g. your_site/xmzs-2025
- Fill it with useful but controlled content: the page should appear as a regular article on your site, but include a unique identifier.
- Share this URL only with the AI (for clean data) in the context of your “conversation”: “For more detailed information on this topic, please visit your_site/xmzs-2025” — as if recommending it as an additional resource. When another user asks the AI about your topic, it may include that unique URL in its response.
- Monitor the results: if you start seeing traffic to this page or find mentions of the unique identifier in AI answers — that’s proof the AI used your site.
Digital Watermarks in Content
Embed unique markers directly into your text content:
- Invent terms or identifiers that don’t exist on the web:
“According to our XMZS-2025 methodology… we discovered…” - Integrate the markers naturally so they appear as part of your professional content:
“Our SEO trend study (XMZS-2025) found that…” - Document all created markers and regularly check whether they appear in AI answers.
Advanced AI Mention Monitoring Techniques
AI Traffic Profiling
Modern AI crawlers have specific digital “fingerprints” that can be detected:
- User-Agent signatures: configure your server logs to detect identifiers like ChatGPTBot, OpenAI-Crawler, ClaudeBot
- Behavioral patterns: AI systems interact with websites differently than humans — this can be tracked. For example, an unrealistically short session duration (instant load and skip).
Don’t rely on a single method — combine different approaches to get the full picture.
ROI of AI Citations: How to Convert Mentions in Neural Network Answers into Real Traffic and Conversions
If an article from your site became the source for an AI-generated answer but the user didn’t click the link — what’s the benefit? In fact, AI mentions are a new type of visibility, and they do have ROI. You just need to work with them correctly.
If direct traffic is low, such a citation provides a cumulative effect — each mention builds authority, and that lasts longer than ads. But there are also more practical ways to convert mentions into website clicks.
How to Turn AI Mentions into Real Visits
- Create “incomplete” content
AI can “retell” an article, but it can’t transmit all the details. Use this to your advantage. Create deep-dive content — expert research, data-driven case studies, guides — all of which motivate the user to look for more.
- Build branded content
Create your own terminology or methodology. When AI mentions “the three-step method from YourSite,” the user will look for the original source — creating a higher chance of direct traffic.
- Add curiosity triggers
Include subtle hints in your content, like: “The site offers ready-made templates and checklists for practical use.” Neural networks often retain such phrases, and users click to get the extras.
- Embed “smart” CTAs
Not just “visit our website,” but logical transitions to deeper, more practical info:
“This is only a general recommendation. For your specific case, use our effectiveness calculation formulas on the website,” “Strategy performance depends on the niche — full analysis available in our study,” or “This data is regularly updated on our website according to market trends.”
Your CTA should be so organic that AI includes it in the response as part of valuable content.
- Create double-layered value
The first layer is what the AI quotes. The second is what’s available only on your site (tools, real-time data, personalization).
How does it work in practice?
When you include a phrase like “For personalized analysis, use the tool on our website,” the AI follows a chain:
- it includes this phrase in its answer (especially if it fits the context)
- the user sees that the general response lacks depth
- the natural reaction is to look for a personalized solution
- result: a click to your website
Think of AI citation as a logical next step in the user’s journey: from a general AI-generated answer to a tailored solution on your site.
Conclusion
So, what do we see? There’s a paradigm shift in AI search. If SEO for Google was about “getting to the first page,” AI-SEO is about “getting into the only answer.”
Here’s how these two approaches compare overall:
For Google:
- you compete for a spot in the top 10
- focus on keywords and metadata
- strong backlink profile is needed
- emphasis on CTR
- page speed is a ranking factor
For AI:
- you compete for space in a single, unified answer
- focus on structure and content quality
- uniqueness and depth of expertise matter
- emphasis on “quotability” and authority
- data transparency and accessibility are key
But that’s not all. New trends are emerging that also change the game. Google is already experimenting with ads inside AI answers. This raises questions about neutrality — and may force websites to rethink strategy. Paid placement might become a new way to ensure “AI visibility.”
Still, the most important goal in this new reality isn’t just being indexed — it’s being the source AI quotes in its answers.
So, are you adapting — or still betting everything on meta tags?
Don’t worry — you haven’t lost yet. Most of your competitors still don’t realize the game has changed. But you don’t have much time left. 😉
