Service
Ongoing AI Visibility Monitoring
Re-run the identical benchmark on a fixed schedule so movement is attributable and drift is caught while it is still small.
The problem this addresses
Something changed. You do not know what, when, or whether it was you.
AI recommendation behaviour moves for reasons that have nothing to do with you: a vendor ships a model update, a competitor earns a citation, a directory changes how it syndicates. Without a fixed measurement running on a schedule, none of that is visible until it has already cost you work.
Monitoring re-runs the same frozen prompts, on the same platforms, in the same geography, every cycle. Because nothing about the test changed, a change in the result means something in the world did.
Alongside the benchmark we watch the things that move between cycles: your reviews and reputation, your entity facts drifting out of date, and the technical health that determines whether you can be read at all.
What it includes
- The frozen benchmark re-run each cycle, with full evidence capture
- Score movement against baseline and the trailing 90 days
- Platform-by-platform comparison
- Competitor movement and share of voice
- Source and citation changes
- Review, entity-accuracy and crawler-health checks between cycles
- A prioritised plan for the next period
What you receive
A cycle report showing current score, baseline, 90-day trend, platform differences, competitor movement, source changes, work completed and the plan for the next period.
What this does not do
Monthly cycles are a sample, not surveillance. We measure on a schedule and report what the schedule caught; we do not claim to observe every answer every consumer receives.
How this is measured
Every service sits inside the same measurement loop. Work is proposed from recorded evidence, and its effect is assessed by re-running the identical benchmark rather than by asserting that it must have helped.
Usually paired with
AI Recommendation Baseline →
Find out whether AI assistants currently recommend your business, who they recommend instead, and which sources they relied on to decide.
AI Visibility Optimization →
Improve the signals that affect how AI systems find, read and understand your company — then re-measure to see whether it worked.
Every engagement starts with a measurement
Tell us about your business and we will establish where you currently stand.