Track How AI Engines Describe Your Brand Over Time
AI brand tracking measures how often your brand appears in AI-generated answers, how it is characterised, and which sources are cited — scan after scan, so the trend is visible.
Why AI brand tracking needs its own measurement
A rankings report tells you where a page sits on a results list. It does not tell you whether an answer engine mentioned you at all when a buyer asked which vendors to consider. Those are different questions, and only one of them now sits between your brand and the shortlist.
Answers are also unstable. The same question, asked a month apart, can return a different set of brands as models are updated and as the sources they draw on change. A single check is a snapshot; tracking is what turns it into a signal a marketing leader can act on.
BrandOptics runs a consistent, persona-modelled question set on a repeating schedule so each result is comparable with the last. What changes in the report is a change in the market, not a change in how the question was asked.
What is tracked in every scan
Visibility trend over time
Each scan records how often your brand appears in answers to the questions your buyers actually ask, so movement month over month is visible rather than anecdotal.
Citation frequency and sources
See which pages and third-party sources the engines cite when they describe your category, and where your own material is being passed over.
Persona-modelled questions
Questions are modelled on your buyer personas and competitive set rather than drawn from live user data, so the same benchmark can be re-run consistently.
Competitive share of answer
Track how your competitive set is described alongside you, and which of them the engines reach for first.
How BrandOptics tracks a brand
Define the question set
We model the questions your buyers ask from your personas, category and competitive set.
Run the scan across engines
The same question set is run across the AI engines included in your plan — Gemini, OpenAI ChatGPT, Perplexity, Anthropic and others depending on configuration.
Record mentions and citations
Every mention, omission and cited source is captured against that scan date.
Compare against the last scan
Each new scan is benchmarked against the previous one, turning AI brand tracking into a trend rather than a snapshot.
Question sets are modelled on personas and competitive context; they are not sourced from live user queries.
Common questions about AI brand tracking
What is AI brand tracking?
AI brand tracking is the practice of repeatedly measuring how AI answer engines describe your brand — how often you are mentioned, in what terms, alongside which competitors, and which sources they cite — so changes can be observed over time instead of guessed at.
How is it different from traditional brand monitoring?
Traditional monitoring counts mentions on pages and in media. AI brand tracking measures what a generated answer says, which is synthesised from sources the engine chooses. A brand can be widely written about and still be absent from the answer.
How often should a brand be tracked?
Monthly is the practical cadence for most brands. Model updates and source changes move results enough that a monthly benchmark shows real movement, while more frequent scanning mostly captures noise.
What does it cost to start?
Self-serve tracking starts at $40 per month for one domain and one engine. The $89 plan covers three engines. Enterprise engagements cover a custom number of domains, engines and analyst review.
Start tracking your brand in AI answers
Begin with a self-serve plan, or talk to us about an enterprise engagement with analyst review.