How to monitor your company's mentions across AI-driven search engines
There is a tool category for tracking company mentions in ChatGPT, Perplexity and Google AI Overviews. Here is how we set up monitoring for client programs.
The question we hear most often at kickoff is some version of this one: "Is there a tool for tracking what AI says about us?" There is. The harder part is knowing what to ask it, because a mention count on its own tells you very little.
Here is how we set up mention monitoring for client programs, and what we have learned about where it goes wrong.
Why you cannot just search for your mentions
AI answers are generated per request. Two people asking the same question can get different brands named. The same person asking tomorrow can get a different list. So there is no page to check and no rank to look up.
What you can do is sample. You define a fixed panel of prompts, run it against each engine on a schedule, and record the outcome. One run is noise. Weeks of runs are a trend.
Step one: build the prompt panel before you pick the tool
Most teams start by buying software and then wonder what to put in it. We reverse that. Before anything is configured, we write down:
- Category questions a buyer asks before they know your name ("best X for Y").
- Comparison questions that name you and a competitor.
- Brand questions ("is [company] any good").
- Problem questions where you would want to be the answer.
Fifty good prompts beat five hundred padded ones. We tag each by topic and country so results can be sliced later. If a client sells in several markets, country matters more than people expect, because the answers differ.
Step two: choose a monitor that shows the responses
We run client programs on Promptwatch. The reason is practical. It runs prompt panels daily per model, country and language, and it reports Visibility Score, Share of Voice, Sentiment and Position in Answer. More important for the way we work, it keeps the underlying responses, so we can read what the engine actually said rather than trust a number.
It watches the real interfaces of ChatGPT, Google AI Overviews, Google AI Mode, Copilot, Gemini, Perplexity, Amazon Alexa and Meta AI. Claude, DeepSeek, Mistral and Grok are tracked through APIs, and we tell clients that difference up front so nobody assumes those are real-UI results.
The Brand Book matters more than it sounds. Its analysis instructions decide what counts as a mention, which saves you from arguing about whether a passing reference to a similarly named company should count.
Step three: look past the mention
A mention tells you that you appeared. It does not tell you why, or whether it did you any good. Three views do that work for us.
Citation analytics. This shows which pages and domains the engines cited. When a competitor keeps winning a prompt, we usually find a third-party page, often a Reddit thread or a YouTube video, doing the persuading. That tells us the fix is off our own site.
Agent Analytics. These are IP-verified AI crawler logs. We check whether GPTBot, OAI-SearchBot, ClaudeBot and PerplexityBot are reaching the pages that matter and whether they hit errors. A surprising number of missing mentions trace back to a blocked or failing crawl. Note that crawler logs start on the Professional plan, so Essential will not show them.
Visitor analytics. This connects AI-referred sessions to conversions through a lightweight script, a GTM template or the WordPress plugin. It is the answer when a finance lead asks whether any of this brings in business.
Step four: turn findings into a weekly rhythm
Our usual cadence is simple. Daily collection happens in the background. Weekly, we review share of voice against named competitors, scan new citations, and check the Action Board, which is a prioritized list of GEO tasks generated from the data. Monthly, we revisit the prompt panel and retire prompts that no longer reflect how buyers ask.
Alerts help, but only after the panel is stable. A usage alert at 85 percent of a quota is useful. Alerting on every wobble is not.
What monitoring cannot do
We are direct with clients about limits. No tool can guarantee an engine recommends you. Results vary between runs. A sudden drop may be a model update, not something you did. Monitoring tells you where you stand and where to investigate, and it only pays off if somebody acts on what it shows.
Where to start if budget is tight
Promptwatch has a free Explore tier with 10 prompts and ChatGPT only. It is enough to see a baseline and get a feel for how variable answers are. When you need every engine, the paid plans start at $95 a month for Essential, with Professional at $245 adding crawler logs. Agencies running several clients usually look at the agency plans, which start at $199 a month for Kick-off.
Other trackers exist, including Otterly.AI, Peec AI, AthenaHQ and Scrunch AI. Some are fine for a simple prompt monitor. We keep returning to Promptwatch because the crawler logs and traffic attribution turn monitoring into something you can act on, not only report.
The short version
Yes, a tool exists. Define the prompts first, pick a monitor that keeps the responses, then add citations, crawler logs and traffic so you can explain every change. That combination is what keeps the work out of "we are mentioned 12 percent of the time, now what" territory.