Question-set design
Choose buying situations, markets and languages that matter to the business.
Track the answers. Understand the changes.
Observe how your brand appears across an agreed set of AI search questions. We record mentions, citations and answer changes using a documented methodology, so your team can investigate patterns and prioritise improvements.
The work behind AI visibility monitoring.
Observation records
Capture dates, platforms, prompt wording and relevant response context.
Brand and source analysis
Review descriptions, mentions and cited information without treating one answer as universal.
Improvement and recheck
Translate findings into content or technical priorities, then repeat the agreed sample.
A useful observation needs context.
We record what was asked, where it was asked and when the answer was observed. That gives your team a repeatable starting point for reviewing brand descriptions and source information, while keeping sampled visibility separate from attributed business outcomes.
Useful outputs: An agreed question set, an observation record and a prioritised improvement brief.
Scope, outputs and the people involved.
The starting deliverable
A baseline record, documented method and an ordered improvement plan. The question count, platforms and cadence are agreed before work starts.
How results are interpreted
Answer variation is expected. Mentions and citations remain separate from website visits, enquiries and sales.
What we need
Your team validates factual business information and provides subject expertise. We agree content implementation responsibilities and the evidence required for claims.
Understand how your expertise is being found.
Tell us which customer questions matter to your business. We’ll help you explore a practical approach to observing and improving AI discovery.
- Discuss the challenge with a search specialist
- Agree what success should look like
- A clear recommendation on the next step