Resources
LLM Visibility Audit Checklist.
The questions a team should answer before investing in AI search visibility.
01 / The approach
Clarity is a
competitive asset.
A useful LLM visibility audit starts with a disciplined checklist: the audience, prompts, current sources, evidence gaps, technical accessibility, ownership and an agreed decision after the audit.
The questions a team should answer before investing in AI search visibility. The point is to create a source system that a real buyer can use: an answer should lead to evidence, a next question or an appropriate conversation—not merely repeat a claim.
02 / What the work covers
Defined with scope, owner, evidence requirement and a way to decide whether the work improved the journey.
Defined with scope, owner, evidence requirement and a way to decide whether the work improved the journey.
Defined with scope, owner, evidence requirement and a way to decide whether the work improved the journey.
Defined with scope, owner, evidence requirement and a way to decide whether the work improved the journey.
We do not treat a platform mention, a citation or a ranking as a standalone outcome. The useful measure is whether the brand is represented accurately for commercially relevant questions and whether the team knows what to improve next.
03 / Questions to resolve
define the question panel before taking screenshots
Document the evidence, source pattern and decision that sit behind this question. That makes the work reviewable instead of dependent on a single tool or output.
record sources, not only mentions
Document the evidence, source pattern and decision that sit behind this question. That makes the work reviewable instead of dependent on a single tool or output.
separate content, entity and technical gaps
Document the evidence, source pattern and decision that sit behind this question. That makes the work reviewable instead of dependent on a single tool or output.
turn findings into an owned, prioritised work register
Document the evidence, source pattern and decision that sit behind this question. That makes the work reviewable instead of dependent on a single tool or output.
04 / Where it fits
Part of a wider
source system.
This work complements SEO, brand, product and communications teams. The right sequence depends on the gap: sometimes the first priority is an audit; sometimes it is documentation, a market guide, expert evidence or the technical architecture that makes existing knowledge retrievable.
Good work leaves a team with decisions it can defend: which pages need an owner, which claims need evidence, which sources matter, which markets require a different approach and what should be measured next. A platform result or a model mention is an observation—not the strategy.
Use the market hubs to see how the method changes with a real buyer journey. We only create a market-specific programme where it has its own evidence model and practical commercial purpose.
What this work does not promise
It does not promise a guaranteed citation, a fixed AI ranking or control over a third-party model. It improves the quality, clarity and retrievability of the source system that a buyer and an answer product can use.
Primary references
Platform behaviour changes. These official sources support the principles on this page and should be checked alongside the date and context of any audit.