The short answer. Submit the prompts your buyers actually use to the major AI assistants — ChatGPT, Claude, Gemini, Perplexity — and record whether your brand appears, where it ranks and how it is described. Most companies have no process for this, which means they do not know whether assistants are recommending them, ignoring them, or steering buyers straight to a competitor.
What does monitoring your brand in AI answers actually mean?
Traditional brand monitoring tracks mentions in news, social and review sites. This is different. It tracks what an assistant says about your category when a buyer asks a question — and whether your brand appears in that answer at all.
When someone asks an assistant "what's the best project management tool for remote teams", the answer names two or three vendors. Those vendors get the consideration. Everyone else does not exist in that moment.
So the process is:
- run the prompts your buyers actually use;
- record which brands the assistant names, and in what order;
- note the sentiment and framing around each mention;
- track how all of that moves over time.
Repeatable measurement, not a one-time check.
Why can't I just ask ChatGPT about my brand directly?
You can, and you should — but "tell me about [Brand]" is not how buyers meet you. They ask job-to-be-done questions: how do I reduce customer churn, what tool tracks AI search visibility, which platform should I use for B2B content analytics.
Your brand can look confident in a direct brand query and be completely absent from every category and use-case prompt. That gap is where the revenue is lost, and only the unbranded prompts find it.
Doing it properly needs four things:
- A prompt library built around real buyer questions, not your brand name.
- Coverage across models — each has different training data, retrieval logic and citation behaviour.
- Structured scoring — presence, position, prominence, sentiment.
- Competitive context — who is named when you are not, and why.
How do AI assistants decide which brands to mention?
Crawlable, indexed content. Retrieval systems pull from pages they can reach. If your site blocks GPTBot, ClaudeBot, Google-Extended or CCBot, your content cannot be retrieved at citation time, however good it is.
Source authority. Models weight industry publications, analyst sites, encyclopaedias and review platforms. A brand with broad third-party coverage has a structural advantage over one with equivalent product quality and thinner external presence.
Intent-matched content. Asked "how do I track brand mentions in ChatGPT", a model looks for content that answers exactly that. Product pages do not. Pages framed around the specific question do.
Recency. For anything with a retrieval component, recently published and recently updated content reads as relevant. Cadence matters.
How is this different from SEO monitoring?
SEO monitoring tells you where you rank on a results page. AEO monitoring tells you whether you appear in the answer — a different output, measured differently.
| Dimension | SEO monitoring | AEO monitoring |
|---|---|---|
| What is measured | Rank position on a SERP | Presence in a generated answer |
| Query type | Keyword | Natural-language prompt |
| Competitive set | Every ranking page | The brands the model names |
| Sentiment | Not applicable | Positive, neutral or negative framing |
| Surfaces | Google, Bing | ChatGPT, Claude, Gemini, Perplexity |
A team watching only traditional search is not watching the surface where a growing share of B2B research now starts.
How do I find out why a competitor gets cited and I don't?
This is the most actionable question in the whole discipline, and it is answered by looking at sources rather than at scores.
- Run the prompt that produces a competitor mention and not yours.
- Identify the citations behind that answer.
- Audit them — what kind of content, published where, saying what?
- Map the gap: do you have an equivalent page, is it crawlable, is it indexed?
In most cases it resolves to one of three things: they have content addressing the use case and you do not; their content is reachable by AI crawlers and yours is not; or they have stronger third-party coverage that the models treat as authority.
Frequently asked
How often should I run the prompts?
Monthly at minimum. If you are publishing against a gap, run them before and after each push so the change is attributable. Weekly during an active campaign.
Do I need every assistant, or just ChatGPT?
At least ChatGPT, Claude, Gemini and Perplexity. Citation behaviour differs enough that one model is a misleading sample.
How long before new content shows up in answers?
For retrieval-augmented models, days after indexing. For models answering from training data, longer and less predictable. Crawlable and indexed maximises both paths.
What is the most common reason a brand is missing?
Blocking AI crawlers — usually without knowing. If content cannot be crawled it cannot be cited, and no amount of quality compensates.
Where Flare fits. Flare is an AEO console that runs this process for you: one prompt set to eight assistants, every answer scored for presence, position, prominence and sentiment into a single 0–100 score, benchmarked against the competitors the models actually name, with the citations behind each answer attached and a content brief for each gap. A classic-search baseline runs alongside it, so you can tell whether you are losing the AI answer, the search result, or both.
Related: what is AEO, or what Flare does.