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AI Visibility Tracking

Know exactly how often ChatGPT, Perplexity, and Google AI Overviews name your brand, and watch the trend move.
Steve Lee, Founder of SEO Aesthetic·Written July 14, 2026·Updated July 30, 2026·5 min read
On This Page
  1. 1. What it tracks
  2. 2. How it works
  3. 3. Reading the trend
Summary & Key Takeaways
  • Tracks how often each engine names you for the prompts you choose.
  • Reports the trend over time, because a single prompt on a single day is noise.
  • Benchmarks your visibility against named competitors.
  • Turns “are we doing AEO” into a number you can watch.

1. What it tracks

You define the prompts your buyers actually ask, the real questions they put to an engine before they ever land on a website, and the platform records how often each engine names you in the answer. That share of voice across ChatGPT, Perplexity, Google AI Overviews, and Gemini rolls up into a single AI visibility score, with all the detail kept underneath it: which prompt, which engine, named or not, and who got named instead. The score exists so a non-technical stakeholder can see movement at a glance, and the detail exists so your team can act on it. It is the core measurement that the rest of Answer Engine Optimization steers by, the one number that answers the question every executive now asks: when someone asks the AI about our category, do we come up?

2. How it works

The platform runs your prompt set across the major engines on a schedule and logs whether you were named, alongside the competitors who were named in your place. The discipline is in the sampling. Answer engines are probabilistic: the same prompt can return a different set of sources an hour later, so a single check tells you almost nothing and a single screenshot is the easiest number in this industry to fake. The system runs each prompt repeatedly and aggregates across runs to produce a stable signal with its variance visible, rather than a daily coin flip dressed up as a metric. That is the difference between knowing your real standing and reacting to noise, and it is why a one-prompt demo from a cheaper tool should make you suspicious, not impressed.

3. Reading the trend

The number that matters is the direction over weeks, not the reading on any given day. A rising trend means your topical authority is compounding, your entities are resolving cleanly, and the corroboration behind your claims is landing where engines can see it. A flat or falling trend is not a failure, it is a map: it tells you which prompts, which topics, and which competitors to push against next. That signal does not just sit on a chart. It feeds straight into the data feedback loop, where the gaps the trend exposes become the next set of things to fix, so measurement and action stay on one thread instead of living in two tools nobody reconciles.
An experiment I ran
I tracked one brand from invisible to cited and timestamped the exact moment it flipped

On a [national B2B] brand we instrumented AI visibility from day one of the AEO program, before we had moved anything at all. For [weeks] the brand was named in roughly zero percent of answers for its target prompts. Flat zero. We kept grinding on entity consistency and corroboration, and kept sampling every single day, waiting for something to move.

The flip was not gradual, it was a step change. Right around the point where the entity finally stabilized across the web, visibility jumped and then held. Without continuous tracking we would have missed both that it happened at all and what set it off. The timestamp is the whole insight: it tells you exactly which work moved the needle, instead of leaving you to guess.

If you only measure quarterly, you see that it changed. You never see why.

HOT TAKE · THE PART NOBODY SAYS OUT LOUD
A visibility score with no prompt set behind it is pure theater

Any tool on earth can show you a big number labeled AI Visibility. The only question that makes it mean anything is: visibility for which prompts? A score untethered from a specific, buyer-relevant prompt set is a vanity metric in a KPI’s clothing.

The actual work is choosing the prompts that map to actual purchase intent, then tracking your share of voice on exactly those and nothing else. Visibility for prompts no human ever types is worthless. The prompt set is the real product here. The number is just the readout on the dial.

WHY THIS BEATS THE PASTE-AND-SHIP SHOPS
Curating the right prompts is the senior work every cheap tool skips

The commodity approach auto-generates a generic prompt list from a keyword tool and tracks whatever falls out. It looks like coverage on the dashboard. It mostly tracks queries your buyers have never once typed, producing a beautiful, clean chart of completely irrelevant visibility.

Choosing prompts that reflect how real buyers ask an engine for a recommendation is judgment work, done by US-based operators who actually understand the category and the funnel, not a list auto-expanded from a handful of seed keywords. The first measures what matters to the business. The second measures whatever was easy to scrape.

Tracking the wrong prompts perfectly is still tracking the wrong thing.

See your AI visibility score live.
Book a demo and we will run your prompts across the major engines and show exactly where you are named today.
Book a Platform Demo
Frequently asked questions
Which engines are tracked?
ChatGPT, Perplexity, Google AI Overviews, and Gemini, with the set growing as engines emerge.
Why track a trend instead of a single result?
Engines sample and shift constantly. The honest signal is the direction over weeks, not any one prompt on any one day.
Can I choose the prompts?
Yes. You define the buyer prompts that matter, and the platform tracks your share of voice on them.
References
  1. 1. OpenAI. ChatGPT search documentation.
  2. 2. Perplexity. Publisher and citation documentation.
  3. 3. Google. AI Overviews and generative search experience documentation.