A tool to monitor how your brand shows up in AI-generated summaries and overviews: what we use

Clients rarely ask us for "a tool". They say something closer to: we think AI is summarizing our category without us in it, can you check. That is the right instinct, and the answer starts with a method rather than a product. The product matters, but only after the method is clear.

Start with the questions, not the dashboard

An AI summary is a response to a prompt. Before you monitor anything, you need the prompts. We build them from four places: what sales hears on calls, what customers type into support, the head terms the site already ranks for, and the comparison questions buyers ask when they are close to deciding ("X versus Y", "best X for Z").

Then we group them by topic and by who is asking. A procurement lead and a founder phrase the same need differently, and AI engines answer them differently. Grouping by country matters too, because the cited sources shift with location.

Keep the first set small. Fifty good prompts beat five hundred vague ones, because you will read the results, and reading is the point.

What to watch in a summary

When we review how a brand shows up, we look at five things in each answer:

1. Is the brand named at all?
2. Where in the answer, first recommendation or a footnote at the end?
3. What is said about it, and is it accurate?
4. Which sources does the summary cite?
5. Who else is named next to it?

A mention rate alone hides most of this. A brand that is named in 60 percent of answers but always last, with a stale description pulled from an old review page, has a different problem from one that is absent entirely.

Why one run proves nothing

AI answers vary from run to run. Ask the same question twice and you may get different brands. That is why a monitoring tool has to run panels repeatedly and report trends, not screenshots. It is also why we tell clients to ignore a single dramatic answer, good or bad. What counts is the direction over weeks.

The tool we run client programs on

We run client work on Promptwatch, and the reasons are practical.

First, it checks the surfaces clients ask about. Google AI Overviews and AI Mode, ChatGPT Search, Copilot, Gemini, Perplexity, Amazon Alexa and Meta AI are monitored through their real interfaces, with other models covered via API. Runs happen daily by model, country and language.

Second, the metrics fit the five questions above. Visibility Score and Share of Voice give the trend, Position in Answer shows rank within the response, and the per-response sentiment score makes tone visible. The Brand Book is a setting we configure on day one, because it decides what counts as a mention. If a client's brand shares a name with a common word, getting that wrong poisons every number after it.

Third, the explanation layer. Citation analytics show which pages and domains the engines cite, at page and domain level. Agent Analytics shows IP-verified AI crawler logs, so we can see whether GPTBot, OAI-SearchBot, ClaudeBot and others actually reached the pages we expect to be summarized. When a client is absent from AI Overviews, "the crawler never fetched the product pages" is a very different fix from "a competitor owns the comparison page that gets cited".

Fourth, the follow-through. The Action Board gives a prioritized list, and content gap analysis shows prompts where the brand has no good answer page. Clients that want content produced can move into the Content Agent on Business, which writes and publishes against gaps with a review inbox.

On cost, brands start free on Explore (10 prompts, ChatGPT only) and paid plans run from $95 a month on Essential. Crawler logs begin on Professional at $245. For agencies there are self-serve plans at $199, $399 and $799 a month.

A setup that works in the first month

Week one: write the prompt set, configure the Brand Book, add the three to five competitors the client really loses deals to, and record the baseline.

Week two: read every answer for the highest-value prompts. Note the inaccuracies. These are quick wins, because a wrong description usually traces to a page you can edit or a source you can contact.

Week three: connect crawler logs and visitor analytics if the plan includes them, and check which AI bots are reaching the site and which pages get cited.

Week four: turn the findings into five actions on the Action Board and assign owners.

What monitoring cannot do

No tool can promise that an engine will recommend your brand. Monitoring tells you what happened in the sampled runs and points to likely causes. It shortens the path to the fix, and it gives the client a number to track. Anyone who tells you otherwise is selling a guarantee that nobody can give.

If you are shopping for a tool right now, run the free Explore plan on Promptwatch against your ten most valuable buyer questions first. If the answers surprise you, you have your case for a proper program.