05 · Visibility
Your next customer is asking an AI assistant who to hire. Make sure it says you.
Buyers now shortlist through AI assistants before they ever reach a search results page. We find out what those models currently say about you, fix what is wrong, and build the evidence that makes you the recommendation.
- Visibility audit
- Structured data
- Content strategy
- Monitoring
Capabilities
What the programme covers.
Part diagnostic, part content engineering, part ongoing watch.
Assistant audit
We ask the major assistants the questions your buyers ask and record exactly what they answer.
Accuracy corrections
Wrong services, outdated pricing, stale claims, and confusion with similarly named businesses, all traced and addressed.
Structured data
Machine-readable markup so models can state your offering with confidence instead of guessing.
Evidence content
The pages, proof, and third-party signals that make a model comfortable recommending you.
Competitor comparison
Who is currently being named in your category, and why the models favour them.
Ongoing monitoring
Answers re-checked on a schedule, because model behaviour changes without warning.
Outcomes
What improves.
Recommendation rate
You get named more often when buyers ask for options in your category.
Description accuracy
Models describe what you actually sell, at the level you actually operate.
Qualified inbound
People arrive already convinced, because an assistant vouched for you.
Early warning
You find out when a model starts getting you wrong, before it costs deals.
How we build it
How the programme runs.
01
Audit
A structured sweep of assistant answers about your brand, your category, and your competitors.
02
Fix
We implement the corrections: markup, content, positioning, and the external signals within reach.
03
Monitor
We re-test on a schedule and report on movement, so visibility is managed rather than hoped for.
Questions
What clients ask about this.
Find out what AI already says about you.
Most owners are surprised, and rarely in a good way.