SHEKARI · SERVICES
AI search analytics with transparent attribution
Before reporting "AI traffic," the team must distinguish identifiable referrals, official search-feature reporting and manually sampled appearances. This service reviews data sources, channel rules, conversion events and attribution gaps. The output is an auditable measurement framework, not a dashboard that assigns unknown direct traffic to AI by assumption.
When is this service relevant?
Typical situations worth investigating before choosing the next step.
Responsibilities overlap with adjacent services. AI Search Visibility records feature appearances; Analytics examines visits and outcomes actually captured in site-owned tools.
The execution decision can be based on insufficient evidence. Examine available Search Console and analytics access, referrers, valid campaign tags and conversion-event quality.
Findings may be overstated beyond the conditions of observation. Not every interaction provides a trackable referrer. Calling all Direct traffic AI-generated is not defensible.
Scope and potential deliverables
The final scope is agreed after reviewing the website; these are typical work areas.
An auditable source map separating Search Console Generative AI feature reporting, known referrals and site events.
Referrer classification rules and conversion definitions, with unknowns and consent limits documented.
A time-bounded reporting template showing denominators, feature impressions versus referral sessions and tracking QA.
A maintenance and definition-change log, never attributing all Direct traffic to AI.
How the engagement works
The steps are adjusted to the scope we agree on.
- 01
Confirm the audience and scope: Analytics teams struggling with channel definitions or attributing unknown traffic to assistants.
- 02
Gather evidence and establish the baseline: Examine available Search Console and analytics access, referrers, valid campaign tags and conversion-event quality.
- 03
Separate the assignment from neighboring services: AI Search Visibility records feature appearances; Analytics examines visits and outcomes actually captured in site-owned tools.
- 04
Prepare implementation tasks and deliverables: A channel data dictionary, classification rules, reporting template, tracking issues and maintenance plan.
- 05
Review findings and monitor valid indicators: Review classification accuracy, event quality and time-bounded attributable sessions and qualified leads.
IN-DEPTH GUIDE
What is involved in AI search analytics?
Useful details to consider before deciding on this service.
Create an accountable definition of AI-related visits and conversions. AI Search Visibility records feature appearances; Analytics examines visits and outcomes actually captured in site-owned tools. Not every interaction provides a trackable referrer. Calling all Direct traffic AI-generated is not defensible.
Define attributable versus inferred data
A session carrying a known referrer differs from a hypothesized AI exposure. Do not combine them into one misleading figure.
Audit measurement setup
Review event naming, internal traffic, privacy controls and consent restrictions before relying on a dashboard.
Maintain reviewable source grouping
Document recognized referral domains and the date of the definition. Some products do not supply reliable referrer information.
Separate search-feature metrics from referrals
Google launched the Search Console Generative AI performance report in June 2026 and rolled it out worldwide by 31 August. It reports URL impressions in AI Overviews and AI Mode by page, country, device and date. These impressions are not assistant referral visits, click totals or a complete query-by-query record.
Define meaningful conversions
Choose tested events such as qualified form completions or measurable calls rather than equating every pageview with a lead.
Build time-bounded transparent charts
Show numerator, denominator, time window and data availability for each rate. Do not fill unavailable cells with fabricated zeros.
Document attribution blind spots
Private browsing, consent, app-to-browser transitions and absent referrers can weaken attribution. Include those limitations in the report.
Set a maintenance routine
Review new referrers, changed definitions and tracking errors so historical numbers remain comparable.
START A CONVERSATION
Request an AI search analytics audit
Review available reports and conversion events without merging official feature data with referral estimates.
FAQ
Frequently asked questions
A few useful details before we begin.
What is the difference between AI referral traffic and observed visibility?
A session carrying a known referrer differs from a hypothesized AI exposure. Do not combine them into one misleading figure.
Which tracking configuration issues are checked before reporting?
Review event naming, internal traffic, privacy controls and consent restrictions before relying on a dashboard.
How are known AI referrers categorized without overclaiming?
Document recognized referral domains and the date of the definition. Some products do not supply reliable referrer information.
Is Google AI search reporting the same as assistant referral data?
Google launched the Search Console Generative AI performance report in June 2026 and rolled it out worldwide by 31 August. It reports URL impressions in AI Overviews and AI Mode by page, country, device and date. These impressions are not assistant referral visits, click totals or a complete query-by-query record.
Which enquiries should count as actual conversions?
Choose tested events such as qualified form completions or measurable calls rather than equating every pageview with a lead.
What attribution blind spots must be disclosed in the dashboard?
Private browsing, consent, app-to-browser transitions and absent referrers can weaken attribution. Include those limitations in the report.