Use case
AI search visibility tracking
More buyers now ask an AI assistant before they ever search. If ChatGPT or Perplexity recommends three tools and yours is not one of them, you lost the shortlist without seeing a click. A tracking agent asks the engines your buyers' questions every week and tells you where you stand and what moved.
How do I know if ChatGPT recommends my business?
Ask it the questions your buyers ask, many times, and count. A tracking agent sends a fixed set of buyer prompts to ChatGPT, Claude, Perplexity, Grok and Gemini on a schedule, records every answer and cited source, and reports your mention rate against competitors week over week. On Qoren it runs as an always-on agent from the AI visibility tracker template.
The problem
Checking by hand does not work. You type a question into ChatGPT, see your name, and feel fine; a colleague asks the same thing an hour later and gets a different list. Answers vary from one run to the next, differ between engines, and shift as models and their search results change. A single spot check is an anecdote, and nobody has the patience to ask five engines twenty questions three times every week and keep the tally.
How an agent handles it
- Send the same buyer prompts to ChatGPT, Claude, Perplexity, Grok and Gemini on a schedule, with web search on.
- Ask each prompt several times per engine, so results are rates rather than one lucky answer.
- Record who was mentioned, in what order, and which domains each answer cited.
- Compare each week with the last and flag which changes are real and which are noise.
- Read the answers behind a change and quote any factual error about your business.
- Name the sources that get cited when you are left out, with a concrete move for each.
Why it sells
- A weekly number for how often each engine mentions you, next to your competitors.
- Early warning when an engine starts describing your product wrongly.
- A short list of the pages and listings that would put you in more answers.
How it runs, step by step
Choose the prompts
You and the agent write ten to thirty questions a real buyer types before choosing, such as "best invoicing tool for freelancers" or "alternatives to a competitor". Category questions, where you have to earn the mention, matter more than questions that already name you. Each prompt gets a permanent id, because the prompt set is the time series.
Name the field
The agent records your brand with its aliases and domains, plus the three to eight competitors a buyer would weigh you against. Mentions are scored for every name on that list, so the report shows share of voice rather than your number alone.
The weekly collection
Once a week it asks every engine every prompt, three times each by default, and stores every raw answer and every cited link. Before the first run it shows you the number of calls and the estimated cost, and a per-run cap keeps it inside the budget you approved.
Separate signal from noise
Because answers vary, the agent reports rates such as "mentioned in 27 of 60 answers" and tests each change against the previous week. A move is called a trend only when it is larger than normal run-to-run variation. Everything else is labeled as noise, however tempting the story.
Read the answers
Counting names is mechanical, so the agent does the part a counter cannot: it reads the answers behind every change. It checks how you were described, why a competitor took the first slot, and whether a mention was a real recommendation or a passing aside. It also fixes its own alias list when it finds a miss.
The Monday brief
One page lands in your inbox or channel: mention rate per engine with last week's rate, the prompts you gained or lost, any factual error quoted exactly, the domains cited in answers that left you out, and up to three recommendations tied to a prompt and the evidence behind it.
When this is not the fit
This measures what the engines say through their APIs with web search on. That makes it a consistent panel for tracking trends and sources, not a copy of what a person sees in the consumer apps, which can layer on memory, personalization, their own instructions and their own search behavior, and can name different brands as a result. It also does not change what the engines say by itself: it tells you where you are missing and what to fix, and the fixing is content and listings work you or your team still do. For a business whose buyers never ask an AI assistant, classic search tracking is the better use of money.
Templates to deploy for this
Start from a ready-made agent and tailor it to the client. Each one runs on a managed environment, online on schedules and triggers.
Ai Visibility Tracker
Tracks whether ChatGPT, Claude, Perplexity, Grok and Gemini mention your business when buyers ask, how often, and which sources they cite, week over week
Competitor Watchdog
Watches competitor sites, pricing, changelogs, and job boards, and you hear about it only when something changes
Reputation Manager
Every review gets a drafted reply within the hour, every brand mention seen, sentiment digested weekly
Demand Scout
People describing your problem, found daily across Reddit, HN, and X, with a help-first reply drafted for each, ready to post.
Frequently asked questions
ChatGPT, Claude, Perplexity, Grok and Gemini by default, each queried with web search on. You can switch an engine off or change which model stands in for it, and the agent proposes a model update when a provider releases a newer one.
Related use cases
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