SHEKARI · SERVICES
Audit source URL visibility in AI search interfaces
The unit of observation here is a destination URL, not a brand name inside an open-ended model conversation. For a fixed query set, we check whether a site page appears among visible AI search sources and record the context of each observation. Brand mentions in conversational answers belong to LLM Visibility; the Google AI Overview feature also has a dedicated analysis service.
When is this service relevant?
Typical situations worth investigating before choosing the next step.
Responsibilities overlap with adjacent services. LLM Visibility samples model conversations; AI Search Visibility checks identifiable search interfaces and page URLs.
The execution decision can be based on insufficient evidence. We collect priority URLs, query set, region, language, device and indexation context.
Findings may be overstated beyond the conditions of observation. AI feature appearance is not constant across users or queries.
Scope and potential deliverables
The final scope is agreed after reviewing the website; these are typical work areas.
A fixed query/target-URL/surface matrix with market, language and device context.
An evidence ledger separating AI feature occurrence from the target URL appearing as a source.
Indexing and text-access checks for target pages, tied to observed gaps.
Prioritized follow-up tasks and a repeat-sampling plan that documents unstable results.
How the engagement works
The steps are adjusted to the scope we agree on.
- 01
Confirm the audience and scope: Sites needing an evidence-led view of important pages within AI-powered search interfaces.
- 02
Gather evidence and establish the baseline: We collect priority URLs, query set, region, language, device and indexation context.
- 03
Separate the assignment from neighboring services: LLM Visibility samples model conversations; AI Search Visibility checks identifiable search interfaces and page URLs.
- 04
Prepare implementation tasks and deliverables: A query/URL/feature observation ledger, supporting samples, coverage gaps and review priorities.
- 05
Review findings and monitor valid indicators: Compare target-page appearances in a repeatable set and relevant page trends, with conditions clearly stated.
IN-DEPTH GUIDE
What is involved in AI search visibility audit?
Useful details to consider before deciding on this service.
Set the target queries and URLs, then record the interface, date, country and device. Label feature presence separately from source URL appearance and produce a reproducible issue list rather than a guaranteed ranking.
Define a stable test boundary
Choose a bounded list of commercially relevant pages and questions. Shifting the denominator invalidates easy month-over-month claims.
Record market and device context
Location, language, account state and device can change the visible features. Capture relevant conditions with each result.
Separate a feature from a citation
Seeing an AI Overview on the page does not mean your site was linked as a source. Label feature presence and site appearance independently.
Check the page’s technical context
Indexability, HTML content and answer quality help interpret opportunities, though a missing appearance rarely has one provable cause.
Observe competing sources fairly
Where other sources appear, record their page type and evidence level without claiming to know their overall feature share.
Archive reviewable observations
Keep date, question and shown URLs with screenshots or text notes as permitted. Avoid recording user-private data.
Interpret variation cautiously
A change in sample appearance is not proof of additional traffic. Search and referral measurements require separate checks.
Turn observations into tasks
Assign the target URL, suspected content or access issue and next test. Do not build a new page merely because one sample lacked a citation.
START A CONVERSATION
Request an AI search URL audit
Set target URLs, queries and market to document when a page appears as a visible AI search source.
FAQ
Frequently asked questions
A few useful details before we begin.
Which AI search surfaces are included in the visibility audit?
Choose a bounded list of commercially relevant pages and questions. Shifting the denominator invalidates easy month-over-month claims.
Why must country and language be fixed for visibility checks?
Location, language, account state and device can change the visible features. Capture relevant conditions with each result.
Does an AI Overview appearing mean our page was a source?
Seeing an AI Overview on the page does not mean your site was linked as a source. Label feature presence and site appearance independently.
How is the target URL checked before interpreting visibility?
Indexability, HTML content and answer quality help interpret opportunities, though a missing appearance rarely has one provable cause.
How is observed source visibility archived for later review?
Keep date, question and shown URLs with screenshots or text notes as permitted. Avoid recording user-private data.
What decisions can a page visibility audit actually support?
Assign the target URL, suspected content or access issue and next test. Do not build a new page merely because one sample lacked a citation.