Know what AI says about you — and what to do about it
Your buyers ask an assistant before they ask you. CiteCue asks the same questions on a schedule, records whether you were named, who was named instead, and which sources the answer trusted — then turns the gaps into a ranked list of changes worth making.
What AI visibility monitoring is
AI visibility monitoring is the practice of repeatedly asking AI assistants the questions your buyers ask, then measuring whether your brand appears in the answer, how prominently, which sources the answer cites, how you are described, and what share of the category’s mentions you hold.
The repetition is not optional. Answer engines are non-deterministic — the same prompt can return a different answer minutes apart, naming a different set of brands. A single check in a chat window tells you what happened once. Monitoring tells you the rate, and a rate is the only thing you can watch move after you ship a change.
The five things worth measuring
Each answers a different question, and a good week on one can hide a bad week on another. Tracked together they describe a position; tracked alone, any one of them misleads.
| Metric | The question it answers | What a reading means |
|---|---|---|
| Mention rate | How often are you named at all? | The share of tracked prompts whose answer mentions your brand. The baseline number — everything else is conditional on being in the answer. |
| Recommendation position | When named, are you first or fourth? | Where you land when the answer lists several brands. Being third in a list of three is a materially different result from leading it. |
| Citations | Which sources back the answer? | The pages an engine links as evidence. Often someone else’s roundup rather than your own site — which tells you where the work actually is. |
| Sentiment | How are you described? | Whether the framing around your name is positive, neutral or negative — and whether the claims made about you are even accurate. |
| Share of voice | How much of the category is yours? | Your mentions as a proportion of all brand mentions across the prompt set. The one metric that moves when a competitor gains, not just when you slip. |
Monitored across the engines people actually use
Assistants disagree with each other. A brand that leads one engine’s answer can be absent from another’s for the same question, because they retrieve from different sources and weight them differently — so which engines you scan matters as much as how often.
- ChatGPT
- Perplexity
- Google AI Mode
- Google Gemini
- Microsoft Copilot
- Grok
- DeepSeek
- Anthropic Claude
- Google AI Overviews
Those 9 are the engines the platform can scan, covered in full on the Enterprise tier. Self-serve plans scan a subset — ChatGPT, Gemini and Perplexity are the core coverage, and which of them a project gets, at what cadence, depends on the plan. Current per-plan coverage is on the pricing page.
What the monitoring actually gives you
Prompt tracking
You choose the questions — the ones with buying intent, not a keyword list. CiteCue runs them on a schedule and records, per prompt and per engine, whether you were mentioned, in what position, and against which competitors. Because the same prompt is asked repeatedly, a drop shows up as a trend rather than an anecdote.
Not sure which questions matter? The prompt set generator drafts buying questions from a short description of your brand, and this guide covers how to choose them.
Share of voice and competitor benchmarking
Share of voice is your mentions as a proportion of every brand mention across your prompt set. It is the metric that catches the case your own numbers miss: your mention rate held steady, but a competitor doubled theirs, and the category moved without you.
CiteCue breaks that down topic by topic, so a loss is attributable rather than atmospheric — you can see which questions a competitor owns, and the sources doing the work for them.
Citations and the sources behind the answer
An answer that recommends you is usually built on somebody else’s page — a roundup, a review site, a forum thread. Knowing which domains an engine leans on for your category is often more actionable than your own score, because it tells you where a mention needs to exist before the engine will repeat it.
Sentiment and factual accuracy
Being named is not automatically good. CiteCue records how you are characterized by platform and topic, and flags claims made about you that are simply wrong — outdated pricing, a discontinued feature, a limitation you no longer have. Those are correctable, and correcting them is usually faster than earning a new mention.
From measurement to a ranked list of fixes
A dashboard that reports a score drop without naming a cause leaves the hard part to you. CiteCue’s audit report closes that gap: every head-to-head loss is scored across 13 factors, and the factors you are missing become an ordered queue — highest expected impact first, with the specific page and the specific change named.
Detect
Commercially relevant questions run across the engines on your plan, surfacing missing mentions, lost citations, inaccurate claims, crawler problems and competitor advantages.
Explain
The answer, its cited sources, the affected prompts and the competitor evidence are kept together, scored across 13 citation factors — so a loss has a named cause rather than an inferred one.
Fix
The finding becomes a specific action: a content change, a technical fix, an outreach or community task, or an agent-usability problem to resolve.
Publish or hand off
Supported changes go out through AI Auto-Fix or an approval workflow. Technical work you would rather own can be exported as an implementation-ready prompt for a coding agent.
Prove
A later scan checks the original success condition. Publishing a change is not the same as improving visibility, so the verification stays inside the loop.
The queue itself is on every plan. From the Pro plan up CiteCue also drafts each change for you, and on Agency, Autopilot prepares them after every scheduled scan — always behind an approval step, never published unreviewed.
Reporting to clients? Building a client-ready AI visibility report walks through turning a scan into a report someone will actually read.
What monitoring can’t do
Worth stating outright, because the opposite gets promised often in this category.
- No tool can guarantee a recommendation. Answer engines do not sell placement, and their source selection is not directly controllable. Anything promising guaranteed inclusion is describing something other than how these systems work.
- Monitoring is not the improvement. Measuring your position changes nothing by itself. The gain comes from the work the measurement points at — clearer pages, corroborating third-party evidence, consistent facts, reachable content.
- Variance is real. Two scans of the same prompt can disagree. That is a property of the systems, not a defect in the measurement, and it is why single readings are reported as part of a rate.
- Fixes apply to what you control. CiteCue drafts and serves changes to your own properties. It does not edit third-party sources, and buying mentions is not something it will help you do.
Go deeper on any module
Prompts Monitoring
Track the buying questions themselves, across engines and over time.
Learn more →Citations & Competitors
Who gets cited, who wins each topic, and the 13 factors behind it.
Learn more →Sentiment & Brand Risk
How AI characterizes you, and which false claims need correcting.
Learn more →AI Readiness
Whether AI crawlers can reach and parse your pages at all.
Learn more →Agent Usability
An AI agent attempts real tasks on your site and reports where it fails.
Learn more →Content Fixes & Autopilot
Factor gaps become a prioritized, ready-to-apply queue.
Learn more →AI Auto-Fix
Serve llms.txt and AI-optimized page variants automatically.
Learn more →Common questions
- What is AI visibility monitoring?
- AI visibility monitoring is the practice of repeatedly asking AI assistants the questions your buyers ask, then recording whether your brand is mentioned, where it ranks among the brands named, which sources the answer cites, how you are described, and how much of the category’s total mentions you hold. Because AI answers are non-deterministic, it is a measurement of rates across many samples rather than a single lookup.
- How is it different from SEO rank tracking?
- Rank tracking tells you the position of a URL on a results page a user still has to click. AI visibility monitoring tells you whether your brand appears inside an answer the user may never click through from, and which third-party sources that answer was built on. The two overlap — being crawlable and well-structured helps both — but a page can rank first in search and never be named by an assistant.
- How many prompts should I track?
- A workable starting point is 25 to 50 prompts covering your main buying questions, reviewed weekly. Fewer than that and normal answer-to-answer variance swamps any real change; many more than that, before you know which prompts matter commercially, mostly adds noise and cost.
- Can CiteCue guarantee my brand gets recommended?
- No, and no tool honestly can. Answer engines do not sell placement and their rankings are not directly controllable. CiteCue measures where you stand today, identifies the specific gaps behind each loss, and drafts the changes to your own site and published evidence that make you a better candidate to cite.
- Which AI engines does CiteCue monitor?
- The platform can scan 9 answer engines: ChatGPT, Perplexity, Google AI Mode, Google Gemini, Microsoft Copilot, Grok, DeepSeek, Anthropic Claude, Google AI Overviews. That full roster is Enterprise-tier coverage. Self-serve plans scan a subset, with ChatGPT, Gemini and Perplexity as the core coverage, and the cadence varies too — current per-plan coverage is published on the pricing page.
- How often should I scan?
- Weekly is enough to see direction without over-reacting to variance in individual answers. Scanning daily is useful when you are actively shipping fixes and want to see whether a change landed; scanning monthly tends to be too coarse to attribute a movement to anything you did.
More in the full FAQ, or see how the category compares in Best AI Visibility Tools in 2026.