B2B buyers often form an impression of a company before speaking to sales. They may visit the website, compare suppliers, read technical information, and check LinkedIn pages or employee profiles. As AI tools become part of this research process, the public information around a company becomes even more important.
Recent research from Meltwater analysed 9.5 million AI citations across B2B categories and found that LinkedIn was the second most-cited source after YouTube. The study also found that LinkedIn appeared among the top cited domains across most major B2B categories, that most LinkedIn citations pointed to individual member profiles, and that structured, specific content with clear formatting and concrete examples performed best.
LinkedIn has often been treated as a place for company updates: trade fair announcements, certifications, product news, recruitment posts and occasional event photos. These updates still have value, but LinkedIn can also provide something broader: public evidence of what a company does and where its knowledge sits.
For B2B companies, this evidence can come from several places. A clear company page explains the business in simple terms. Employee profiles show the people behind the company. Posts and comments show which topics the company is active in. Event updates show participation in the market. The aim is not just to post more; it’s to make the company easier to understand.
A practical starting point is to review your LinkedIn company page as if you were a buyer, or an AI tool, trying to understand the business.
Is the company description clear and current? Do employee profiles explain what people actually do? Are the same product, market, and application terms used on LinkedIn and on the website? Do recent posts show real activity, expertise, or customer-relevant topics?
The Meltwater research also gives useful clues about which types of content are more likely to be cited. The most frequently cited examples were not general company updates, but content that helped with decisions: “best of” lists, side-by-side comparisons, and “how to choose” guides.
The format matters too. In the report, plain text posts and articles made up most of the cited LinkedIn content. Text posts led, followed by articles and then video. This does not mean that video or images are unimportant, but it suggests that written clarity is still essential. AI systems need clear words, structure, terms, and facts they can interpret.
Practical tip: Choose three recurring customer questions and turn them into practical LinkedIn posts. For example: compare two common options, explain how to choose between suppliers or solutions, or list the key criteria a buyer should consider. Keep the wording specific, use the same terms customers use, and connect the post to real expertise inside the company. Over time, these small pieces create clearer public evidence of what the company knows and where it can help.