Your sales team hears it on every call now. "I asked ChatGPT for vendors in this space and you weren't on the list." Nobody can say which question was asked, which model answered, or whether the answer will change tomorrow. That gap sits underneath every conversation about LLM brand visibility. A single percentage hides it. Prompts expose it.
Search engines handed you a keyword report. AI engines hand you nothing. No console shows which prompts mention your brand, which ones name a rival instead, and which ones skip your category altogether. Marketers who build that map themselves, even in a spreadsheet, make better calls than teams arguing over averages.
Why prompts decide who gets mentioned
Keywords are short. Prompts are full sentences with context. "Which CRM works best for a 20-person agency that sells retainers?" The model reads the team size, the business model and the use case, then picks a handful of brands. Two prompts about the same category can return two different shortlists. You are named in one and absent from the other.
That is why one overall score misleads. A brand can post a healthy mention rate and still miss every prompt containing "under $500" or "for enterprise." Those are the prompts with a budget attached.
Build your prompt set
Start with 40 to 60 prompts. Fewer than that and one odd answer skews the picture. Pull them from four places.
Sales call notes
Support and onboarding tickets
Search queries rewritten as full questions
Reddit and community threads in your category
Tag each prompt by funnel stage (learning, comparing, buying) and by buyer persona. Ten minutes of tagging saves hours of confusion later.
Write prompts the way buyers type them
Buyers do not type "best CRM software." They type "we outgrew spreadsheets, need something that connects to Gmail, what do people actually use." Keep the vagueness and the constraints. Polished prompts return polished answers that no real buyer ever sees.
Run them across engines, and run them more than once
ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews and AI Mode each pull from different sources. A brand that wins in Perplexity can be missing in ChatGPT. Test every prompt on every engine your buyers use.
Run each prompt at least three times. Answers are probabilistic. One run is an anecdote. Three runs start to look like a signal. For every answer, log whether you were mentioned, where you sat in the list, whether the model cited your domain, and which competitors appeared.
Sort the results into four groups
Won prompts put you early in the answer, ideally with a citation. Protect them.
Shared prompts name you alongside rivals who sit above you. Work on position.
Lost prompts name a competitor and skip you. This is your priority list.
Blind spots return generic answers with no brand named. Nobody owns them yet, and you can.
Find out why you lose a prompt
Open the sources behind the answer. The pattern is usually one of three. A competitor has a comparison page that mirrors the prompt wording. A review site lists them and not you. Or a community thread recommends them by name. Models quote the pages they can reach. If you are missing from those pages, you are missing from the answer.
Check your own site too. Can AI crawlers reach it? Does the page that should answer the prompt state the answer in its first two sentences? Pricing, use cases and integrations buried in a PDF or behind a form are invisible to the model.
Fix the gaps in order of revenue
Take lost prompts with buying intent first. Publish a page that answers the exact question, with the answer up top, a comparison table and named customer examples. Then earn the third-party mentions the model already trusts by pitching the review sites and list pages it keeps citing. Add structured data and plain entity details (name, category, pricing, who it is for) so models describe you correctly. Re-run the prompt set two to four weeks later and compare.
Make it a weekly habit
Models change. Retrieval sources change. A prompt you won in August can flip by October. Re-run the set weekly, flag every prompt that changes status, and report one number to leadership: the count of high-intent prompts where your brand is named. That figure gets budget approved faster than any impression count.
Doing this by hand works for a month. After that it becomes a part-time job. LLM Search Console runs your prompts across engines on a schedule, shows which ones mention your brand, and flags the ones that move.
Start with five prompts today
Open your CRM, find the last five questions prospects asked before they bought, and run them through ChatGPT and Perplexity right now. Write down who gets named. Then subscribe to the newsletter and get one prompt-tracking teardown every week.