When someone shows me an AI answer that recommends a competitor, I want to read the question before we discuss the response.
“What are the best tools in this category?” is a different assignment from “What should a small team with these requirements use?” Your company might belong in one answer and have no business appearing in the other.
My SEO and AI-search work starts there. Before trying to increase a mention count, I want to know which buying situations we're trying to understand.
Inspect the comparison
Here's a hypothetical example. You sell software that requires a considered implementation. A competitor appears in an answer about inexpensive tools someone can start using this afternoon.
The absence of your product could be entirely reasonable. Pushing your way into that answer might attract the wrong expectations. Change the question to include integration requirements, team needs, and the problem the buyer is solving, and you have a more useful comparison to inspect.
I would read the descriptions, too. Being mentioned sounds positive until the answer misstates what the product does. A response that sends the right buyer away because of an outdated limitation deserves attention even if a visibility dashboard counts the mention as a success.
Save enough to investigate
For a small manual check, I'd keep a record of the question, answer, model, date, and cited sources. I'd also note whether the session had prior context that could affect the response. Then I'd repeat the relevant questions to see which issues recur.
For a useful handoff, I’d add the exact statement that needs attention and what the current product documentation says. For example: an answer describes a required integration as unavailable, while the documentation shows how it works. The task is to check where that mismatch recurs and whether the relevant sources need correction. “Improve AI visibility” is too broad an assignment for that finding.
The point is to make the observation inspectable. “AI doesn't recommend us” is hard to act on. “These answers repeatedly describe an old product limitation, and two cite this page” gives the team something concrete to investigate.
Review the cited pages before assuming they're the cause. A citation tells you what the answer points to; it doesn't give you a complete account of how the model produced the response. Still, an inaccurate or obsolete source can be a useful place to start.
Turn an answer into work
If the answer reflects unclear information on your own site, improve that explanation. If it relies on an outdated third-party description, identify the relevant correction process. If the comparison favors a capability your product doesn't offer, bring that back as a positioning or product question.
These are different assignments. They need different owners. A content team cannot write its way around a genuine product limitation, and a product team shouldn't be asked to react to a single unrepresentative response.
After making a change, repeat the same checks and preserve the new answers alongside the old ones. Report what changed in that set of observations. Keep the business question separate: are appropriate prospects discovering you, understanding the offer, and progressing?
A mention doesn't establish a lost or won deal. It can reveal what a buyer may be told before they ever reach your site. That is worth understanding without pretending it answers every attribution question.
The AI-search worksheet helps prepare a first set of questions. Start with a buying situation you care about, then read the whole answer.