AI visibility is not simply whether a chatbot knows your company name. The commercially useful question is whether your brand appears when prospective customers ask the kinds of questions that influence a purchase.
A proper AI visibility audit therefore starts with customer intent, not vanity prompts.
Start with the questions buyers actually ask
Build a small set of prompts around the decisions that matter to your business. Include questions such as:
- Which providers solve this problem?
- What is the best approach for this use case?
- What should I look for when choosing a supplier?
- How much does this type of service cost?
- What are the alternatives?
- Which provider is suitable for a business like mine?
Use wording a real customer would use rather than repeatedly asking an AI system to describe your own brand.
Record more than a yes or no
For each prompt, capture:
Google's current guidance for generative AI search keeps the emphasis on established SEO foundations, unique value and useful content rather than special “AI ranking” tricks. Evidence, entity clarity and a crawlable internal structure matter more than cosmetic AI optimisation.
- whether your brand is mentioned;
- where it appears in the answer;
- how accurately the business is described;
- which competitors appear;
- which websites or sources are cited where the platform exposes them;
- whether the answer points towards the category, problem or service you want to own.
A mention with the wrong description can be less useful than no mention at all because it reveals an entity or positioning problem.
Compare the sources behind the answer
When competitors are cited and you are not, inspect the pages that appear to support them.
Look for differences in:
- topical coverage;
- clarity of product or service information;
- third-party evidence;
- structured business information;
- customer proof;
- crawlability and indexation;
- how directly important questions are answered.
Do not copy the competitor. Identify the information gap.
Repeat the test over time
AI-generated answers are not fixed rankings. Results can vary by platform, prompt, model update, location and available source material.
That means one manual check is a snapshot. The useful signal comes from repeated measurement across a defined set of commercial questions.
Digital Womble's AI Visibility check is designed to turn that process into a clearer benchmark so businesses can see where they appear, where competitors are being surfaced and which gaps deserve attention.
Connect AI visibility to website work
AI visibility is not a separate universe from search and content. The underlying work often includes improving the same assets that help people understand and trust the business:
- clear service and product pages;
- strong topical coverage;
- crawlable, indexable content;
- attributable evidence;
- consistent brand and entity information;
- useful third-party references where earned.
If your website does not clearly explain what you do, who you serve and why your claims are credible, an AI system has less dependable material to work with.
Do not turn the audit into a citation chase
The objective is not to manufacture mentions. It is to become a stronger, clearer source on the subjects that matter to your buyers.
Start with the gaps that connect to revenue: high-intent questions where competitors appear and your brand is absent or misrepresented.
Then improve the underlying pages, evidence and discoverability before measuring again.
Run an AI Visibility benchmark if you want a structured starting point rather than checking prompts manually one by one.
Apply the idea without creating more noise
Start with the page's actual job and the reader's next decision. Check the evidence already available, identify the gaps preventing that decision, and improve those before adding another page or campaign. A useful change should make the journey clearer, not simply make the estate larger.
Measure the result against a baseline. For informational content that may mean qualified impressions, clicks and progression to a relevant commercial page; for commercial content it should extend to enquiries, sales or another meaningful conversion. This keeps optimisation tied to business value rather than publishing volume.
Implementation and measurement
Treat the recommendation as a decision process rather than a publishing task. Define the page or campaign's intended audience, the problem it should solve and the next useful action before changing anything. Compare the current experience with that job, then prioritise the smallest changes that remove genuine friction or ambiguity.
Use evidence at the point it matters. Primary guidance can establish factual constraints; first-party data, examples and experience can explain what those constraints mean in practice. Internal links should expand a concept or move a qualified reader to the next relevant step, not exist simply to increase link counts. The anchor should make the destination understandable before the click.
After implementation, record a baseline and review the metric that matches the job. Discovery work should improve qualified visibility; educational content should create useful progression into deeper or commercial pages; conversion work should be judged on enquiries, sales or another meaningful outcome. Avoid claiming causation from a single short observation window.
This also creates a maintenance loop. When products, evidence, search behaviour or official guidance changes, refresh the affected passage and its linked destinations rather than producing another overlapping URL. That keeps the estate coherent and reduces the risk of thin, stale or competing pages.