It’s no longer necessary to debate whether AI platforms are here to stay. The web has already changed. People are now reaching websites via AI-generated answers, often with refined intent and expectations to confirm, compare, or complete an action. César Canteiro Current Scenario for AI Platform Data Analysis Lately, assistants like ChatGPT, Perplexity, Claude, and Copilot have become a new layer of discovery: they answer questions, cite and link content, and many users arrive at your site from these responses (or return after copying/pasting the link). This is traffic with pre-refined intent, influencing content strategy, SEO, UX, and even paid performance. If you don’t measure it, you miss demand signals and optimization opportunities. With this shift, it’s essential to track traffic coming from these platforms. This traffic is valuable but still “invisible” in traditional reports: GA4 and GSC don’t yet offer a native AI channel. Without isolating these visits, they get lumped into “referral,” “direct,” or even “organic,” distorting editorial, SEO, and media decisions. The practical solution today is to map the referrers/sources from these platforms, create a dedicated GA4 channel, and monitor it in Looker Studio. We’ve already shared tips on identifying long-tail queries in Google Search Console generated from AI interactions. Today, let’s see how to extract insights via GA4, and consequently in Looker Studio. The strategy is simple: capture sessions where the medium is “referral” and the source matches the domains of these AI platforms. With a consistent filter and a dashboard comparing trends, landing pages, and conversions, you can understand the role of AI in content discovery and business generation. What You Can Measure Today in GA4 In GA4, the quickest shortcut is to create a Comparison in Acquisition reports: keep only sessions where the medium is referral and the source matches a pattern of AI domains. This immediately provides insights on sessions, users, landing pages, and events. If you track conversions on another domain (booking engine, checkout, portal), enable cross-domain tracking to preserve attribution. How to Turn It Into Its Own Channel (“AI Referrals”) in GA4 To avoid reapplying filters across every report, create a custom channel grouping. Duplicate the default grouping, add a rule called AI Referrals, and set it so that whenever the source matches AI domain patterns (and optionally the medium is referral), GA4 classifies it in this channel. From then on, AI Referrals appears alongside Organic, Direct, Social, Paid, etc., including in first-click and last-click attribution reports. Step-by-step to create the AI Referrals channel in GA4: Admin (gear icon in footer) → Data Settings → Channel Groups. Click Create Channel Group (or + New). Copy from the Default Group (recommended) and give it a clear name, e.g., “Channels – with AI Referrals.” In the builder, click Add Channel. Channel Name: AI Referrals Condition 1 (SOURCE): Field: Source Operator: matches RegExp Value (regex): see code below Case-insensitive: enabled (if option available) Condition 2 (optional, but useful): Field: Medium Operator: exactly matches Value: Referral Drag the AI Referrals channel above “Referral” in the list (order matters; evaluation is top-down). Save and publish the channel group. Note: This group doesn’t replace the default. You can choose which to use in reports. Accessing AI Traffic in Reports Open any acquisition report, filter by source, and the data will appear. At the top of tables, in the dimension selector (usually “Default Channel Grouping”), switch to your custom group: Channels – with AI Referrals. Important Tips: Cross-domain tracking: if conversion occurs on another domain (booking engine/checkout), configure cross-domain measurement to maintain attribution. Retroactivity: custom channel groups classify reports (including previous periods) as GA4 processes data; they don’t alter raw data or Ads integrations. How to Measure AI Traffic in Looker Studio In Looker Studio, replicate the same logic directly in a chart or table: a filter that includes medium=referral and source matches the regex below. This allows you to build a clean view over time, by AI source, landing page, first vs last click, engagement, and conversions. Example: Simple daily pageviews chart for users coming from AI platforms Regex to filter AI platforms in Looker Studio and GA4: HTML.*chatgpt.com.*|.*perplexity.*|.*edgepilot.*|.*edgeservices.*|.*copilot.microsoft.com.*|.*openai.com.*|.*gemini.google.com.*|.*nimble.ai.*|.*iask.ai.*|.*claude.ai.*|.*aitastic.app.*|.*bnngpt.com.*|.*writesonic.com.*|.*copy.ai.*|.*chat-gpt.org.*.*chatgpt.com.*|.*perplexity.*|.*edgepilot.*|.*edgeservices.*|.*copilot.microsoft.com.*|.*openai.com.*|.*gemini.google.com.*|.*nimble.ai.*|.*iask.ai.*|.*claude.ai.*|.*aitastic.app.*|.*bnngpt.com.*|.*writesonic.com.*|.*copy.ai.*|.*chat-gpt.org.*HTML Case-insensitive and update as new sources appear. Even without a native channel, you can answer practical questions: how much traffic comes from AI, which pages they prefer to cite, how this audience behaves, and how much converts. This is enough to guide content strategy, SEO, and UX with real data while preparing for when GA4 and GSC officially support this category. Make good use of it!
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