A New Place Buyers Meet You
B2B buyers increasingly start supplier research by asking an AI assistant: “who are the main providers of X for companies like ours?”, “what does Company Y do?”, “Y or Z for a 100-person firm?”. The answer arrives before they ever reach your website, and it shapes the shortlist.
You cannot control what an AI assistant says. You can find out what it says, correct what is wrong at the source, and make it easier for these systems to describe you accurately. For a B2B brand, the aim is not to “rank” in a chatbot. It is to be described correctly, in the right category, when a qualified buyer asks.
What Can Go Wrong
When we look at how AI assistants describe B2B companies, the same problems come up:
- Missing. The brand is not mentioned at all for category questions where it should be a contender.
- Mis-categorised. The assistant places the company in a neighbouring category, so it appears for the wrong buyers and not for the right ones.
- Out of date. Old pricing, a retired product name, or a service the company no longer offers.
- Confused with someone else. A similarly named company’s details are blended in.
- Over-claimed. The assistant says you offer something you do not, such as a certification or an integration, which surfaces later as a disappointed buyer.
How to Check It Yourself
A basic check takes under an hour and needs no tools:
- Write a short prompt panel. A dozen questions a real buyer might ask, across four types: your brand by name, your category (“best X providers for UK firms”), comparisons (“you versus a named alternative”) and problems (“how do I fix the problem you solve?”).
- Run each prompt on the main assistants. ChatGPT, Claude, Gemini and Perplexity, each in a fresh session, signed out where possible so your history does not colour the answer.
- Record the answers verbatim, with the date. Answers change over time, so a dated record is what lets you see progress.
- Mark each answer. Were you mentioned? Recommended? Described correctly? Placed in the right category? Which competitors appeared instead?
Our step-by-step walkthrough goes into more detail. If you would rather not do it by hand, the free AI Visibility Signal runs a 12-prompt panel across ChatGPT, Claude, Gemini and Perplexity and returns a 0–100 score graded A to E, in under an hour.
Fix the Sources AI Reads
AI assistants describe you from what they can read about you. The most reliable fixes are at the source:
- One clear definition page. A page that says plainly what the company is, what it does, who it is for, and what it is not. Plain sentences beat clever ones here.
- Consistent facts everywhere. Company name, category, services, locations and prices should match across your website, LinkedIn, Companies House, directories and review sites. Contradictions get blended into the answer.
- Structured data. schema.org markup for your organisation, services and frequently asked questions helps machines read the facts on your pages.
- Comparison and alternatives pages. If buyers ask “you versus Z”, an honest, factual comparison page on your own site gives assistants something accurate to draw on. Keep it fair and verifiable: UK advertising rules apply to comparisons.
- Evidence others can cite. Named case studies, published methods and clear, dated facts are more likely to be repeated accurately than slogans.
- An llms.txt file. A proposed convention: a plain-text file at the root of your site summarising who you are and linking to your key pages. It is not a standard every assistant reads, but it is cheap, and it forces a clear summary.
Measure It Over Time
Re-run the same prompt panel on a fixed rhythm, monthly or quarterly, and keep every answer with its date. Track a small number of measures: how often you are mentioned, how often you are recommended, how often you are described correctly, and which competitors appear in your place. Changes take time to show, because assistants update on their own schedules. A dated log is what lets you tell a real improvement from noise.
The goal is accuracy, not volume. Content written only to be picked up by AI, with claims you cannot support, is the same problem as an unsupported claim on your homepage, just harder to correct later.
Where This Fits in Go-to-Market
AI visibility is not a separate channel to bolt on. It reflects how clearly your positioning is expressed across everything you publish. If assistants describe you in the wrong category, the root cause is usually that your own site does not say clearly enough what you are and who you are for. That is a positioning problem first.
Start with a free AI Visibility Signal to see where you stand. If the fix means rebuilding how the company is described, the Go-to-Market Build delivers a 5-page website or landing page, a 20-slide sales deck and a 3-email sequence built on tested positioning, written to be read accurately by buyers and AI assistants alike.
Common Questions
What is AI visibility?
Can we control what AI assistants say about us?
How often should we check?
Does llms.txt help?
What does the free AI Visibility Signal include?
Sources and Further Reading
- schema.org — Organization, Service and FAQPage types.
- llmstxt.org — the proposed /llms.txt convention (J. Howard, 2024).
- Advertising Standards Authority / CAP — The CAP Code, section 3, on comparisons with identifiable competitors.
