When a customer asks an AI system for a recommendation, there are several questions worth separating. Did your business appear? Was it described accurately? Which sources supported the answer? Did a person arrive at your site and take a useful next step?
Peekaboo, one of the products I build, tracks brand mentions, competitors, sentiment, and cited sources across AI search experiences. That gives a marketing team material to investigate. A mention is an observation. It needs more context before it becomes a business conclusion.
My starting point is a small set of customer questions and a record of what the systems return. It is easier to choose useful work when you can see the answer and the evidence behind it.
Choose questions customers actually ask
Use discovery calls, support requests, sales conversations, and customer research to find the language. A category question, a comparison, and a question about suitability reveal different things. “What tools track AI search visibility?” differs from “Which option fits a small agency reporting to clients?”
Record the wording, audience, platform, and observation date. Repeat a consistent set so you can compare changes. Add exploratory questions when useful, but distinguish them from the recurring sample. Otherwise a changed measurement set can look like a changed market position.
Be explicit about what the sample represents. A handful of prompts cannot describe every customer, location, or answer a system might produce. Use the sample to find patterns and follow-up questions.
Inspect descriptions and sources together
When your brand appears, read what the answer says. Does it describe the current product? Does it confuse your company with another? Does it point to a relevant page? A favorable mention with an incorrect capability can still create a poor customer experience.
When another business appears, examine the cited sources and the criteria in the answer. Those observations may suggest a documentation gap, an unclear product page, or a useful comparison your audience needs. They are clues to investigate. They do not prove which change caused a recommendation.
Keep dated evidence and the source links with your notes. If a claim is inaccurate, trace it where possible and correct the information you control. Record other sources that need attention rather than assuming a rewrite of your homepage will fix every answer.
Make your website useful for the next question
Google's official guidance says its existing SEO practices remain relevant to AI Overviews and AI Mode. It does not require special AI files or dedicated schema to appear in those features. Eligibility still depends on ordinary search requirements, and inclusion is not guaranteed.
That points toward practical work: make important information available as text, connect pages with useful internal links, and make structured data consistent with visible content. Check that crawlers can reach the intended pages and that the product information is current.
For the reader, add the details that support a decision: who the product fits, the problem it solves, actual capabilities, limitations, and a clear next step. A concrete walkthrough or original explanation can answer a question more effectively than another broad article about the category. Google's people-first content guidance supports that focus on usefulness and demonstrated knowledge.
Connect the observation to a business outcome
Visibility research should sit beside website and customer evidence. Ask whether visitors understand the offer, whether inquiries fit the work you want, and what customers say influenced their decision. Use the tracking and analytics available to your business, and state attribution limits when the path is incomplete.
Choose one change with a written reason. It might be correcting a capability, improving a comparison page, or publishing a source-backed walkthrough. Keep a dated change log and continue observing the same question set. Several things can change at once, so describe a movement as an observation unless you have evidence for causation.
Keep the next step concrete
A useful first deliverable is a short visibility brief: questions reviewed, accurate and inaccurate mentions, sources worth checking, and the next changes to investigate. No one can promise placement across every AI answer.
The workflow audit below helps turn that research into a repeatable process. Start with the customer's question, show the evidence, and make the next action clear.