ChatGPT SEO: How to Make Your Website Discoverable by AI

The New Question Everyone Is Asking

The way people find information online is changing faster than ever. ChatGPT and other AI assistants have introduced a new way to discover content, often called AI search or AI-powered discovery. Instead of scrolling through long lists of results, people now ask complete questions and get clear, conversational answers based on web sources.

This shift doesn't mean SEO is gone. Search engine optimization still determines which pages appear in Google or Bing, but AI visibility has become a new layer on top of it. ChatGPT looks for information it can understand and trust, favoring content that is clear, structured, and reliable. This emerging practice is often described as AEO, or AI Engine Optimization. This entails preparing websites to be understood and referenced accurately by language models.

That change has raised an important question among marketers, developers, and business owners:

"How do I rank in ChatGPT?"

It's a fair question, and not an easy one. There is no public algorithm or ranking system, and no official guide that explains how ChatGPT selects or cites content. What we can do is observe patterns and test what makes some websites appear more often than others.

Our team at PrestaChamps spent months researching this topic, analyzing hundreds of ChatGPT responses and comparing the types of pages it recommends.

We studied the technical and content factors that seem to influence visibility and found recurring signals that align closely with SEO best practices, but adapted for the age of AI Engine Optimization. This article shares what we’ve learned: what is known, what remains uncertain, and what can be reasonably assumed about improving a website’s visibility in AI-driven search.

What We Know – How ChatGPT Gets Its Information

Before understanding how to appear in ChatGPT, it’s important to know how it gathers information. ChatGPT does not crawl the web on its own like Googlebot. When it retrieves live data, it relies on search connectors (often Bing or other integrated engines) to access publicly available web pages in real time.

That means AI discovery depends on two layers:

1. Search engine results, which reflect traditional SEO factors.
2. Interpretation and reasoning, where ChatGPT analyzes relevance, clarity, and factual accuracy.

The system looks for structured data and semantic cues to identify what a page contains. Schema markup, descriptive metadata, and consistent formatting make a site easier for AI to interpret. It also relies on the underlying search ranking, which is still influenced by SEO fundamentals like backlinks, freshness, and page authority.

From observation, the pages that appear most often in ChatGPT answers share several qualities:

• The content is clear and easy to read.
• Facts are consistent across multiple sources.
• The site appears reliable, recent, and secure (HTTPS).

In short, ChatGPT may not have a visible ranking index, but its ability to find and recommend web content still depends heavily on strong SEO foundations supported by clarity, structure, and trustworthy information.

What We Don’t Know – The Black Box Part

Much of how ChatGPT decides what to show or recommend is still unclear. OpenAI and Microsoft have not shared any official ranking criteria, and most of what is known comes from observation rather than documentation. The process is still a black box, making it difficult to separate assumptions from proven behavior.

Some of the biggest unknowns include whether domain authority influences visibility, how recency is balanced with trustworthiness, and whether ChatGPT keeps a short-term memory of reliable domains. Interestingly, tests show that the system often recommends pages from websites with a low authority score, suggesting that content quality, structure, and clarity might outweigh traditional SEO authority signals.

It is also uncertain how attribution works. ChatGPT often summarizes or blends multiple sources into a single answer, so a website’s content can influence a response without being cited directly. There is still no public equivalent to Google Search Console for AI systems, leaving visibility inside ChatGPT largely a matter of testing and pattern analysis.

What We Can Assume (with Evidence)

Although the inner workings of AI search remain mostly hidden, certain patterns appear consistently across hundreds of observed ChatGPT and Perplexity responses. The same kinds of websites tend to be cited or summarized repeatedly, and the behaviors point to a clear set of preferences.

AI systems generally prioritize content that is:

• Readable - written in clear, natural language without keyword stuffing or filler phrases.
• Structured - built with schema.org markup, descriptive meta tags, and logical page hierarchy.
• Reliable - accurate, consistent across sources, and supported by visible trust signals like HTTPS and verifiable company data.
• Original - avoids duplication or templated content that feels mechanical.
• Contextually relevant - matches the meaning and intent of the query, not only the literal keywords.

A clear trend is that long, informative pages perform better than short or generic ones. When ChatGPT cites sources, it often links to detailed guides or complete product listings rather than brief descriptions. Pages that combine text, data, and structured elements give the model enough context to understand and verify information confidently.

Mini Case Study:

In our internal testing across several product categories, pages with around 250–350 words of descriptive text and schema.org markup appeared in ChatGPT’s cited sources roughly three times more often than shorter listings. While the exact weighting is unknown, the pattern remained consistent across multiple prompts.

These findings suggest that the underlying mechanism behind AI discovery is much closer to semantic SEO - or AEO (AI Engine Optimization) - than to traditional keyword SEO. Clarity, context, and structure are rewarded because they make the content easier for AI to interpret and reuse accurately.

How to Make a Website “Recommendable” by AI

AI systems don’t “rank” websites in the traditional sense, but they still need to decide which pages to trust, summarize, and cite. The sites that appear most often in ChatGPT or other AI search tools share the same characteristics: they are clear, structured, and rich in useful information. Below are the key elements that consistently improve visibility and recommendation potential.

Longer, well-researched product pages tend to perform better in AI systems because they give enough context to confirm accuracy. A short paragraph is rarely enough. Detailed content provides the model with more signals of relevance, trust, and completeness.

Optimize for semantic understanding

AI discovery is based on meaning, not just keywords. The model identifies intent and context, so pages that explain what something is, who it’s for, and why it matters perform better than those written only to fit search phrases.

• Write text that answers practical questions directly.
• Use factual details and measurable attributes — the data points an AI can quote or compare.
• Avoid filler or repetitive adjectives that weaken clarity.
• Organize information logically with structured headings and concise paragraphs.

Semantic clarity helps AI connect your page with the right queries. It is less about keyword density and more about linguistic precision and informational depth.

Maintain visible trust signals

Credibility still matters. A page that appears authentic and consistent across multiple checks is more likely to be cited or summarized.

• Use HTTPS and ensure technical security is visible.
• Keep business information (address, CUI, contact form) up to date.
• Show reviews, transparent pricing, and clear policies for shipping, returns, and data use.

These elements help both users and AI systems confirm that your website represents a real, reliable source of information.

Keep the language human and specific

Even the most structured page loses value if it sounds robotic. AI models prefer language that reads naturally and reflects real expertise.

• Write in a human tone, with complete sentences and natural rhythm.
• Focus on clarity and usefulness, not keyword repetition.
• Ensure every description is unique, informative, and detailed enough to stand on its own.

The combination of authenticity, structure, and factual accuracy makes a website far easier for AI systems to recognize and trust.

Summary

To become “recommendable” by AI, a website needs:

• Clear, well-structured content that machines can interpret easily.
• Comprehensive, informative pages that provide depth and context.
• Reliable metadata and schema that communicate intent.
• Trust signals that verify authenticity.
• Natural, specific language that reads as written by humans.

These principles create the foundation for the kind of content AI assistants prefer to cite and summarize, paving the way for tools or workflows that can help maintain this level of quality at scale later in the article.

Tools That Can Help

Applying all the principles behind AI visibility takes time and consistency, especially for webshops with hundreds or thousands of products. Writing detailed descriptions, optimizing metadata, maintaining structured data, and updating image alt text can quickly become overwhelming without the right tools or technical support.

For stores that want a hands-on approach, our team at PrestaChamps can help with the technical SEO setup that forms the foundation of AI visibility. This includes schema.org integration, performance optimization, proper use of meta tags, and automating structured data across catalog pages. We also assist with system-level integrations that make sure your product data stays synchronized between your webshop and search engines.

If you prefer an automated solution, there are tools designed to handle much of this work automatically. One of the most effective options for e-commerce businesses is RetailorAI — a solution that rewrites and optimizes product pages based on best practices for both SEO and AI discovery. It focuses on:

• Creating long, detailed, and factual product descriptions that help AI systems understand the item’s purpose and attributes.
• Generating optimized meta titles and meta descriptions tailored for search and AI visibility.
• Writing accurate image alt text that improves semantic context and accessibility.
• Enhancing structured data and keyword balance without sacrificing natural language flow.

For webshops that want to stay ahead of the shift toward AI-driven discovery, combining strong technical SEO with an automation tool like RetailorAI provides a complete approach. It keeps content accurate, machine-readable, and consistently optimized, giving your products a much better chance of being recognized and recommended by modern AI systems.

Preparing for the Age of AI Discovery

AI search is not replacing SEO; it’s redefining it. The same principles that once helped sites rank in Google now need to be applied with deeper precision, context, and structure. Visibility in ChatGPT and other AI systems depends on how well your content communicates its purpose — not just to people, but to machines that interpret meaning.

Websites that combine clarity, detail, structure, and trust will naturally rise to the surface in this new ecosystem. For webshops, this means moving beyond short, repetitive product text and investing in long-form, informative pages that make every product understandable on its own.

Whether your team handles optimization in-house or relies on automation tools like RetailorAI, the goal is the same: to make your website transparent, factual, and readable at both a human and a machine level. Those who adapt now will not only stay visible in search but also become part of the next generation of digital discovery.