AI traffic from GA4

AI visibility tells you whether ChatGPT, Gemini and Perplexity mention a brand. AI traffic closes the loop: it shows how many people those assistants actually send to the website, and what they do once they arrive. Once a Google Analytics 4 property is connected, CrunchJunkie can isolate the sessions, engaged sessions, key events and revenue that originate from AI assistants — turning "we're visible in AI" into a number you can put in front of a client.

GA4 records the referring source of every session. CrunchJunkie matches that source against the hosts AI assistants use — chatgpt.com, chat.openai.com, perplexity.ai, gemini.google.com, copilot.microsoft.com, claude.ai, you.com, poe.com and a few others — and groups them as "AI Source". Because the match happens on GA4's own first-party data, it's accurate and needs no tags, scripts or extra tracking. As new assistants gain referral traffic, the source list is kept up to date.

The fastest route is the "GA4 — AI Assistant Traffic" template: in the report builder, choose Google Analytics as the source and pick that template. It comes pre-built with a per-assistant breakdown table and two donut charts (sessions and key events by assistant), plus an AI-written summary. To add it to an existing report, drop in a Table or Breakdown (donut) widget on a GA4 data source and set its dimension to "AI Source". You can pair any GA4 metrics with it — Sessions, Users, Engaged Sessions, Engagement Rate, Key Events or Revenue — to show both the volume and the quality of AI-driven traffic.

Look at three things together. Volume (Sessions, Users) shows how much traffic AI is sending. Engagement (Engaged Sessions, Engagement Rate) shows whether that traffic is genuinely interested — AI-referred visitors often engage more deeply because the assistant has already qualified their intent. Outcomes (Key Events, Revenue) show whether it converts. Comparing the same report period-over-period reveals whether improving a brand's AI visibility is translating into real, growing traffic and conversions.

The AI → Conversions tab inside a client's AI Visibility project closes the loop most tools leave open: it puts the brand's AI-search visibility trend right next to the sessions, conversions and revenue that AI assistants actually drove to the site (from GA4), on the same timeline. You get headline totals (AI-driven sessions, conversions, revenue over the last 90 days), a dual-axis chart overlaying visibility against the metric you pick, and a correlation coefficient — with the number of overlapping days shown, because correlation only means something with enough data. This is deliberately honest. The AI-driven figures count only GA4 sessions whose source is a known AI assistant (ChatGPT, Perplexity, Gemini, Copilot and more), which is a lower bound — GA4 attributes some AI referrals to Direct, so the true number is higher. Visibility carries forward between scans so the line stays readable, but the correlation is computed only on real scan days, and we label it plainly (correlation isn't causation; it's directional evidence, strongest over a longer window). It needs GA4 connected for the client and some scan history to populate. It's the one view that answers "is being visible in AI answers actually making us money?" — something pure AI-visibility tools can't show, because they have no analytics. It's a report widget too, not just a dashboard. Add the "AI → Conversions" source to any report for a KPI band (AI visibility, AI-driven sessions, conversions, revenue, and the correlation) and the visibility-vs-conversions overlay chart — both render in the live report, the shared link and the PDF. Or start from the "AI Visibility — Complete Report" template, which stitches the whole picture together: brand performance, competitors, per-engine breakdown, topics and cited sources, source health, GEO readiness, shopping visibility, and the AI → Conversions section — so a client sees, in one report, both how visible they are in AI answers and the revenue it drives.