If ChatGPT can't describe you, it won't recommend you

When I asked new clients how they found Ninjabot, the answers used to be predictable: an ad, a friend's recommendation, or a social media post. In the months before November 2025, a new answer started to appear.

More and more people told me they found us through ChatGPT. They did not search on Google or click a Facebook ad. They asked an LLM (large language model) for a solution, and the AI recommended us.

AI assistants such as ChatGPT and Perplexity recommend the businesses they can describe with confidence. If your website states who you serve, what problem you solve, what results you deliver and what you charge, the AI can match you to a buyer's question. If your website is vague, the AI leaves you out of the answer.

I think this is the biggest change in business discoverability since 2005. A website built only for Google keywords slowly becomes invisible to the best-informed buyers in your market.

How AI answers replace search results

For fifteen years, clients found you in a simple way. They typed "marketing automation agency" into Google, scrolled through ten blue links, opened five of them and chose one.

AI assistants change that flow. A potential client now asks ChatGPT: "Who are the top three automation agencies for a mid-sized dental practice? Compare their pricing and specialization." The AI does not return a list of links. It uses its training data, can run a live web search, and names three businesses with a reason for each.

The client contacts those three. If you are not on that list, you get no click and no chance. That is harsher than classic Google search.

The numbers point the same way. In November 2025, BrightEdge reported that AI referrals to leading e-commerce brands grew 752% year over year. Perplexity received 780 million queries in May 2025, according to its CEO Aravind Srinivas. In November 2025, OpenAI launched shopping research in ChatGPT. The gatekeepers have changed, and a site optimized for the search engine of 2015 is invisible to the buyer of 2025. A vague site carries a second risk: when an AI misreads it, the AI can recommend you for the wrong thing.

Why AI reads your website differently than Google

Google works like a librarian: it indexes keywords. An AI assistant works like a consultant: it reads for intent, context and reputation, and it recommends what fits the question.

The librarian scans for text strings such as "marketing agency", "London" or "affordable" and hands you everything that matches. The consultant has to justify a recommendation, so it needs specific facts.

Imagine your website says: "Leading marketing solutions for modern businesses. 10 years experience. Contact us." Google sees the keywords and ranks you. An AI consultant that looks for a specific solution finds nothing to recommend. The description is too vague.

Now imagine your website says: "Specialized marketing automation for dental and medical practices ($2M-10M revenue). Certified HubSpot Platinum Partner. 50+ documented case studies. Average ROI 300% in 6 months. Pricing starts at $2,500/mo."

Google might rank this lower because the keywords are niche. ChatGPT sees a specific answer to a specific problem. When a user asks for "the best agency for a dental practice", the AI recommends you because you fit, not because you ranked.

The 3 layers of LLMO (LLM optimization)

LLMO (LLM optimization), also called GEO (generative engine optimization), is the work of making your business easy for AI assistants to understand, trust and recommend. I split it into three layers.

Layer 1: Who you serve and what you solve. AI models hallucinate when your data is vague, and they recommend you with confidence only when it is specific. Look at your headline. "We help companies grow" is noise to an AI. Rewrite your core value proposition with exact detail: "We help B2B SaaS companies with $1M-10M ARR reduce churn by 15% using customer success automation." State who you serve, the problem you solve and your method.

Layer 2: Trust signals. LLMs give more weight to information that looks like a fact. Unstructured testimonials are marketing copy; structured case studies are data. If your "Results" page is a set of quotes such as "Client X loved working with us", an algorithm cannot use it. Rewrite each one as structured data: "Client X (Logistics) saved 40 hours/week and $12k/month. Implementation time: 3 weeks. Tools used: Slack, Airtable, OpenAI."

Schema Markup is structured code that describes your business to search engines and AI systems in a fixed format. Use Schema Markup (Organization schema) to make your facts machine-readable. Then publish deep-dive content. If you write the definitive guide on "Dental Practice Automation", the AI cites you as the expert.

Layer 3: Your digital footprint. AI assistants do not trust your website alone. They look for confirmation across the web. Search for your business on Perplexity. If only your website appears, you have a trust problem. You want Perplexity to cite your LinkedIn page, a Clutch review, a guest post and a Reddit thread.

Get listed on structured directories such as Clutch, G2 and Crunchbase. AI models rely heavily on these sources for "best of" lists. Do not ignore human discussions either: Reddit licenses its posts to OpenAI and Google for AI training. A positive mention in r/smallbusiness carries weight as a social proof signal.

How to get AI to recommend your business in 60 minutes

This is the step-by-step plan I use to improve how AI assistants see my businesses. It takes less than an hour.

1. Run the prompt test. Open ChatGPT with browsing enabled, or Perplexity. Type the prompt your ideal client would use: "Who are the best [your industry] agencies for [your specific niche]?" This is your reality check. If you are on the list, read the reasons the AI gives: that is your competitive advantage. If you are not, study the businesses that are listed. Their digital footprint is the standard to beat.

2. Rewrite your About page. Go to your website and rewrite the H1 and the first paragraph. Remove words such as "world-class", "cutting-edge" and "synergy": an AI treats them as noise. Replace them with hard data: specific industries, outcomes, tools and revenue ranges. Your goal is to make it impossible for an AI to summarize you incorrectly.

3. Add schema to your site. Give the AI hard data about who you are. Use a free schema generator, such as Merkle or technicalseo.com. Select "LocalBusiness" or "ProfessionalService". Fill every field (description, price range, area served) with your new, specific copy. Add your LinkedIn, Clutch and Twitter profiles in the "sameAs" field. Paste the code into your website header. The AI now has a structured fact sheet about your business.

For more on how buyers research vendors in AI assistants, read half of B2B buyers now start in ChatGPT.

Why AI agents will skip businesses that hide their prices

The next step is agent-to-agent business. A human will no longer be the first point of contact. Your client's AI agent (for example, a vendor researcher) will talk directly to your AI agent (for example, an AI qualifier).

Imagine a client tells their AI: "Find a vendor who can build a custom CRM for under $10k." The agent scans the web and lands on your site. If your site states "Custom CRM development starting at $5k", the agent matches you and flags you as a viable option. If your pricing sits behind a vague "Contact us" button, the agent skips you and moves to the next vendor in milliseconds.

Businesses that hide pricing, process or timelines will be filtered out by AI agents before a human sees them. Businesses that publish clear, structured data will get the shortlist. Transparency is the new SEO.

Build a calmer business,Yuri

Frequently asked questions

What is LLMO (LLM optimization)?

LLMO (LLM optimization), also called GEO, is the work of making a business easy for AI assistants such as ChatGPT and Perplexity to understand and recommend. It has three layers: a specific statement of who you serve and what you solve, structured trust signals such as case studies and Schema Markup, and a confirming digital footprint on LinkedIn, Clutch, G2, Crunchbase and Reddit.

Why does ChatGPT recommend some businesses and not others?

ChatGPT recommends businesses it can describe with confidence. A vague website such as "Leading marketing solutions for modern businesses" gives the model nothing to match against a buyer's question. A website that states the niche, revenue range, certifications, documented results and starting price fits a specific request, so the AI can recommend it with a reason.

How can I check if AI assistants recommend my business?

Open ChatGPT with browsing enabled, or Perplexity, and type the prompt your ideal client would use, for example "Who are the best [your industry] agencies for [your niche]?" If your business is on the list, note the reasons the AI gives. If it is not, study the digital footprint of the businesses that are listed, because that is the standard to beat.

Does Schema Markup help with AI search visibility?

Schema Markup gives AI systems a structured fact sheet about a business. Use a free schema generator such as Merkle or technicalseo.com, choose LocalBusiness or ProfessionalService, and fill every field: description, price range and area served. Add LinkedIn, Clutch and Twitter profiles in the sameAs field, then paste the code into the website header.

Should a B2B service business publish its prices for AI agents?

Publishing prices makes a B2B service business visible to AI agents that filter vendors. If a buyer's agent looks for a custom CRM under $10k, a site that states "Custom CRM development starting at $5k" is a match. A site that hides pricing behind a "Contact us" button gets skipped before a human ever sees it.