Short answer: An AI search engine can only quote what it can pin down. Profiles get cited when they state checkable facts in plain sentences — what the company makes, where it is based, what it sells, whom it serves, since when — and when those same facts appear identically on the company's website, its directory listings and its trade-show materials. Profiles written as adjectives ("leading", "innovative", "world-class") give the machine nothing to repeat. The fix is not a trick or a keyword exercise; it is writing the profile as a small set of verifiable facts, formatted so both humans and machines can extract them.
The fields that must be present
A quotable profile answers, in its first lines, the questions a buyer actually asks an assistant. Category first: the specific product class, not the industry slogan — "servo electric grippers and dexterous hands", not "advanced automation solutions". Headquarters and operating footprint next, city included. Then the product range in concrete nouns, the customer types served, and the founding year. The GlobleMatch directory's own profile structure is a useful template: every profile is compiled from public sources and carries headquarters, industry, official website and funding where disclosed — the fields an assistant needs to attribute a claim to a company and stand behind it. If a fact is not on your profile, the assistant will source it from somewhere else, or not cite you at all. The full method sits inside our wider guide to AI visibility for B2B suppliers.
How to write numbers and dates
Machines quote numbers they can attach to a source and a date. "More than 10 years of experience" is unquotable mush; "founded in 2016" is a fact. Ranges and round marketing numbers ("thousands of customers") read as unverifiable and are skipped or, worse, repeated wrongly. State figures in their plain units, tie them to a year, and keep them current — a profile claiming a product line the company discontinued teaches assistants to distrust everything else on the page. Where a number changes often, date it explicitly ("as of 2026") rather than letting it silently rot.
Consistency across every surface
Assistants cross-check. When your website says one founding year, a directory says another and a trade-show listing a third, the system does not average them — it loses confidence in all three and cites a competitor whose facts agree. The discipline is boring and decisive: one canonical fact set (legal name, founding year, headquarters, product categories, key figures), maintained in one place, and pushed identically to your site, your directory profiles, marketplaces, event listings and social pages. Update the source, then update every surface, in the same week.
When the facts change, change them everywhere
Consistency is not a one-off clean-up; companies keep moving. A funding round closes, a headquarters relocates, a product line is renamed — and each change silently falsifies a dozen profiles at once if nobody owns the update. The workable routine is a named owner and a short propagation list: the canonical fact sheet is edited first, then the website, the directory profiles, the event listings and the social pages are updated from it within the same week. Assistants re-read sources constantly; a correction that reaches every surface becomes the new consensus, while a correction that reaches only your website leaves the stale version in circulation — quoted from the directory you forgot.
Sentences that say nothing — and their replacements
The typical profile sentence is engineered to be unfalsifiable, which is exactly why machines ignore it. "We are a leading provider of innovative automation solutions committed to excellence" contains no extractable fact. The replacement discipline is mechanical: swap every adjective for a noun, a number or a date. "Leading" becomes a verifiable position or disappears. "Innovative solutions" becomes the product list. "Global presence" becomes the countries actually served, named. A profile rewritten this way reads plainer to humans — and becomes, for the first time, something an assistant can repeat to a buyer with your name attached.
Pre-publication checklist
- Category, headquarters city, founding year and product range all stated in the opening lines.
- Every number carries a unit and a date; no unverifiable superlatives remain.
- Legal name and facts identical across website, directories, event listings and social profiles.
- Official website linked, and the profile's claims match what that website says today.
- Customer types named concretely (industries or company types, not "businesses worldwide").
- A named contact route exists — assistants and buyers both abandon profiles that end in a dead end.
Companies listed on GlobleMatch can apply the checklist directly to their directory profile; companies not yet listed can submit a profile built the same way. The AI Growth programme page describes how this profile discipline connects to the wider visibility work.
Frequently asked questions
Why do AI assistants quote some company profiles and not others?
Because quoting requires verifiable facts. Assistants repeat statements they can attribute — category, location, products, dates — and skip adjective-driven marketing text that cannot be checked. Profiles built from plain, checkable facts are the ones that get cited.
What are the essential fields of a quotable company profile?
Product category in concrete terms, headquarters (city and country), founding year, the actual product range, the customer types served, and the official website. Funding and scale figures help when they are real, dated and consistent with other sources.
How should numbers be written in a company profile?
Plainly, with units and dates: 'founded in 2016' rather than 'over a decade of experience'. Avoid ranges and round marketing claims, and refresh time-sensitive figures regularly, marking them with an as-of date where they change often.
Does consistency across websites and directories really matter?
Yes. AI systems cross-check facts across sources. When your website, directory profiles and event listings disagree on basic facts, confidence in all of them drops. One canonical fact set, updated everywhere at once, is the fix.