First, verify what actually increased: sessions, users, landing-page views, key events, or orders. An “AI referral” label tells you how analytics classified a visit; it does not prove that a person shopped or bought anything. Compare analytics with server or CDN logs, check source classification and recent tracking changes, then assess landing pages and conversion quality. Without your property’s data, no single cause can be confirmed.
1. Confirm what rose—and where it appears
Compare the spike period with the prior equivalent period. Check whether the change appears in sessions, users, landing-page views, key events, and completed orders. A rise in sessions without a corresponding change in users or meaningful events tells a different story from a broad increase across those measures.
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- Check whether the result is limited to one Analytics property, data stream, report, or dimension.
- Keep measurement scope consistent: do not compare event-scoped channel data with session-scoped source data as though they measure the same thing.
- Record the exact date the increase began and whether it was a gradual change or a sudden step.
These checks establish what moved; they do not establish why.
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In GA4, examine session source/medium and the session default channel group alongside landing page, geography, device category, and relevant conversion events. Look for the actual source hostnames and whether one assistant or several changed. An “AI” label alone is not enough to identify the source.
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Compare the affected landing pages with your usual entry pages. A sharp increase concentrated on one or two unusual pages, locations, devices, or events merits a different investigation from growth spread across normal entry pages and engaged sessions. Neither pattern proves human activity by itself.
3. Check how GA4 classified the visits
Google’s current default channel group documentation defines AI Assistant traffic as arrivals from recognized sources such as ChatGPT, Gemini, Deepseek, Copilot, and Grok. Classification depends on recognized referrer matching, and the default channel group cannot be edited.
Google explicitly places traffic from Google AI Overviews and AI Mode in Organic Search, not AI Assistant. So an increase associated with Google’s AI search features may not appear in the AI Assistant channel.
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For custom channel groups, Google’s custom channel group guidance gives an AI-assistant example that includes sources such as Perplexity. Channel rules are applied in order: a visit is assigned to the first channel whose definition it matches. Check that your custom AI channel sits above Referral and any other channels it could match. Treat Google’s regex as an example to adapt, not a complete or permanent list of every assistant.
Also inspect session source/medium rather than relying only on a channel label. A visit might be reported as AI Assistant, generic Referral, Organic Search, Direct, or Unassigned depending on the available attribution details and your configuration.
4. Look for measurement or site changes at the same time
Review changes near the spike’s start date, including analytics tags, consent behavior, campaign tagging, routing, domains, checkout flow, and reporting configuration. A reporting or implementation change can alter what gets counted or how an arrival is grouped without creating a matching increase in shoppers.
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Google’s traffic-source documentation explains that referrers and campaign values inform source processing. Direct traffic applies when referral-source information is unavailable or the referring source or search term is configured to be ignored. Direct visits do not necessarily override an existing referrer. Campaign values received mid-session are associated with the relevant events; they are not retroactively applied to the existing session.
Compare the change date with your implementation history before attributing the spike to a new source of demand.
5. Compare browser sessions with server and CDN requests
Browser analytics and server or CDN logs record different activity. Analytics sessions generally reflect activity measured in a browser, while logs can also contain requests from automated fetchers and crawlers. Do not add crawler requests to human session counts; use the two sources as separate evidence streams.
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Compare request timing, paths, and volume in logs with the analytics spike. A user-agent string alone does not confirm that a request came from a particular AI service. Verify requests using the relevant platform’s current bot-verification information before labeling them as confirmed crawlers. The distinction between a crawler fetching a page and a person clicking through is also described in this ecommerce industry guide; treat it as secondary context, not a substitute for current platform documentation.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.6. Review referral exclusions without hiding the evidence
Check unwanted-referral settings for domains involved in your own transaction flow, such as a third-party payment processor. Google’s unwanted referrals documentation explains that exclusions can affect attribution, including for returning users when a domain was previously excluded.
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Do not add an AI assistant domain to the unwanted-referral list simply to make reports look tidier. Doing so can remove useful source information from the very traffic you are trying to diagnose.
7. Report only what the evidence supports
Once you have checked measurement, classification, changes, logs, and visit quality, report the result narrowly. State whether the increase is in AI Assistant, generic Referral, Organic Search, or Direct; whether it persists after accounting for measurement changes; and whether engagement, key events, or orders moved with it. If logs indicate automated requests, report them separately from browser sessions. Leave the cause unresolved if the property’s records do not establish it.
Industry-wide figures are not a substitute for your own data. Chartbeat reported that ChatGPT pageviews in its publisher network grew by more than 200% year over year while AI chatbots still accounted for less than 1% of network pageviews in its Q1 2026 report. Those figures describe Chartbeat’s network, not your site or ecommerce referrals specifically; they are not a forecast or benchmark for your traffic. See Chartbeat’s research page.
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