GA4 for AI Traffic

GA4 can classify traffic with ordered custom channel rules; the first matching channel wins. Evidence for this claim GA4 lets editors create custom channel groups from ordered rules, and a session is assigned to the first matching channel. Scope: GA4 custom channel groups; availability and limits depend on the property and product configuration. Confidence: high · Verified: 2026-07-14 Google Analytics: Custom channel groups Its session source and medium dimensions are the basic fields used to inspect where visits originated. Evidence for this claim GA4 exposes session source and session medium as acquisition dimensions for analyzing where sessions originated. Scope: Observable acquisition metadata; traffic without a usable referrer or campaign tag can be unattributed or classified as direct. Confidence: high · Verified: 2026-07-14 Google Analytics: Traffic-source dimensions

TL;DR — GA4 can now show you visits from AI tools like ChatGPT and Perplexity in two ways: a built-in AI Assistant channel that appeared in May 2026, and a custom channel group you set up yourself. The catch nobody warns you about: the order of your channels matters — put your AI channel above Referral or your AI visits get miscounted. And no matter what you set up, a big chunk of AI traffic arrives with no source attached and lands in Direct, so treat the numbers you see as a minimum.

What we’re actually setting up

When someone clicks a link inside ChatGPT, Perplexity, Gemini, or Claude, their browser sometimes tells your site where they came from — and sometimes it doesn’t. When it does, GA4 can label the visit as AI traffic. This article is about getting GA4 to do that labeling well, and then building a report you can actually use.

There are two pieces:

1. The native AI Assistant channel. Google added this to GA4’s Default Channel Group in May 2026. It’s automatic — you don’t set anything up — and it catches visits from recognized AI tools that arrive with a source attached.
2. A custom channel group. You build this yourself. It gives you broader coverage and lets you re-label old data too. It’s the same idea, just under your control.

The first check: do you already see AI traffic?

Before building anything, look. In GA4, go to Reports > Acquisition > Traffic acquisition and look at the Session default channel group view. If you see a row labeled AI Assistant, the native channel is live on your property. That’s your starting number.

The one rule that trips everyone up

If you build a custom channel group, GA4 checks your channels in order and stops at the first match. A visit from chatgpt.com counts as a “referral” — so if your Referral channel sits above your AI channel, every AI visit gets grabbed by Referral first and never reaches the AI channel. Nothing errors. It just quietly miscounts.

The fix: drag your AI channel above Referral. That’s the whole trick.

Why your AI number will look small (and why that’s not a bug)

A lot of AI tools — especially their phone apps — don’t pass along where the visitor came from. When that happens, GA4 has nothing to label the visit with, so it dumps it into Direct, the same bucket as someone typing your address by hand. Studies put the share of AI visits that vanish this way at somewhere between 35% and 70%.

So the AI number you see is the floor, not the ceiling. There’s no setting that recovers those hidden visits — it’s how the web works, not a mistake in your setup. (The deeper “why” behind that hidden traffic is its own topic — this article stays on the hands-on GA4 side.)

Want the exact menu paths, the regex, the Explorations recipe, and the platform-by-platform UTM reality? Switch to the Advanced tab.

Custom channel definitions are ordered, so an earlier broad rule can capture a session before a later AI-specific rule. Evidence for this claim GA4 lets editors create custom channel groups from ordered rules, and a session is assigned to the first matching channel. Scope: GA4 custom channel groups; availability and limits depend on the property and product configuration. Confidence: high · Verified: 2026-07-14 Google Analytics: Custom channel groups Source and medium analysis remains limited to acquisition information that reaches GA4. Evidence for this claim GA4 exposes session source and session medium as acquisition dimensions for analyzing where sessions originated. Scope: Observable acquisition metadata; traffic without a usable referrer or campaign tag can be unattributed or classified as direct. Confidence: high · Verified: 2026-07-14 Google Analytics: Traffic-source dimensions

TL;DR — Two layers: GA4’s native AI Assistant channel (Default Channel Group, added May 13, 2026 — automatic, referrer-only, not retroactive, narrower recognized-source list) and a custom channel group you build (broader, works on historical data, costs one of your 2 standard-property custom-group slots). Channel order is load-bearing: GA4 assigns traffic to the first channel whose definition it matches, so AI must sit above Referral or AI sessions get silently absorbed into Referral. Setup is step one — the payoff is a Free Form Exploration cross-tabbing Session source/medium × Landing page × key events, and an AI segment you can reuse across any report. UTM behavior is platform-specific: ChatGPT increasingly appends utm_source=chatgpt.com; Perplexity, Gemini, and Claude generally don’t. Combining with Search ConsoleA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. is a manual URL-level join (GSC impressions × GA4 sessions on the same landing page), not a native report — and GA4 can’t isolate AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. from Organic Search at all. Everything here measures the referred slice; 35–70% arrives with no referrer and stays in Direct.

The two layers, and what each one actually covers

Since May 2026 there are two distinct ways to see AI traffic in GA4, and it’s worth being precise about what each does.

Layer 1 — the native AI Assistant channel. On May 13, 2026, Google added an AI Assistant channel to GA4’s Default Channel Group. Google’s description: “AI Assistants is the channel by which users arrive at your site from sources like ChatGPT, Gemini, Deepseek, Copilot, or Grok.” Mechanically, when a session’s referrer matches Google’s internal list of recognized AI Assistant sources, GA4 assigns medium ai-assistant and campaign (ai-assistant) and routes it to this channel. Three things to know: it’s automatic (nothing to configure), it’s referrer-only (no referrer, no classification), and it is not retroactive — it classifies going forward from rollout, not your historical sessions. The recognized-source list also isn’t fully published, so treat it as a moving target.

Layer 2 — a custom channel group you build. This is where you get control: broader domain coverage, the ability to re-segment historical data the native channel skips, and a channel that behaves exactly how you define it. The cost is one of your 2 custom channel groups on a standard property (GA4 360 gets 5; the predefined group doesn’t count against the limit), and each group allows up to 50 channels. Most practitioners run both — the native channel for a zero-maintenance baseline, a custom group for the fuller picture.

The one thing neither layer can do: separate Google’s AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. / AI Mode clicks from regular blue-link Organic Search. Google’s channel definitions fold AI-feature clicks into Organic Search, and the referrer is indistinguishable from a normal Google click — so no regex and no custom channel can pull them out. That’s a boundary condition to state and move past; the why behind it is a whole topic of its ownAI traffic attribution is the practice of correctly identifying and measuring website visits that come from AI tools — ChatGPT, Perplexity, Gemini, Claude, AI Overviews, and AI browsers. It's hard because many of those tools strip the referrer header, so the visits land in your analytics as Direct traffic with no source..

The dark-traffic floor, stated once

Before configuring anything, set the expectation: a large share of AI-driven visits — studies put it at 35% to 70% (Loamly’s 446,405-visit sample puts the high end at 70.6%) — arrive with no referrer at all and land in Direct by construction. That’s not a detection failure GA4 could fix; Direct is defined as the “no signal at all” bucket, so referrer-stripped AI visits fall there the same way a typed-in URL does. Nothing you build in this article recovers those. The dark-traffic mechanism (referrer policies, noreferrer, in-app browsers, copy-paste) is covered in depth by the attribution deep dive — I’m stating the headline once and moving straight to what you can instrument.

Session-scoped vs. first-user dimensions — pick the right field before you build

GA4 exposes AI-source data at two different scopes, and mixing them up quietly changes what a report is actually telling you.

• Session source / medium (session-scoped) — records the source and medium for that specific visit. This is the field every configuration step in this article uses: the custom channel’s Source-matches-regex condition, the Exploration in Step 4, and the landing-page report in Step 5. It answers “did this visit come from an AI tool,” which is the question this article’s setup is built to answer.
• First user source / medium (user-scoped) — records the source and medium of a user’s very first visit, and never changes after that no matter how many times they return through a different channel. GA4’s User acquisition report is built on this scope; Traffic acquisition is built on the session scope.

Why it matters here: pull your AI channel into a User acquisition report instead of Traffic acquisition and you’re asking a different question — “how many of our users were first acquired via AI” — not “how many visits this period came from AI.” A returning user who first arrived via organic search and later clicks back in from ChatGPT shows up as AI traffic in the session-scoped view and as Organic Search in the user-scoped one. Neither number is wrong; they answer different questions, and citing one while meaning the other misleads whoever reads the report.

Every report this article builds — the Exploration in Step 4, the landing-page report in Step 5, the conversion comparison in Step 6 — is deliberately session-scoped, because “which visits did AI send, and to which pages” is a session-level question. If you also want the user-scoped answer (“how many of our users’ first-ever touch was AI”), build a second, clearly-labeled Exploration using First user source / medium instead, and don’t merge the two into one table. Google’s traffic-source dimensions documentation covers the full scope distinction across every acquisition dimension, not just source/medium.

Step 1 — check whether the native channel is already live

Reports > Acquisition > Traffic acquisition, switch the primary dimension to Session default channel group, and look for an AI Assistant row. If it’s there, the native classification is running on your property. Wide availability rolled out through early June 2026 (the exact “wide availability” date is secondary-sourced — Google dated the classification logic to May 13 but didn’t separately date the availability milestone), so if you don’t see the row yet, it may still be arriving.

Step 2 — build a custom channel group

Admin > Data display > Channel groups > Create new channel group. (GA4 shuffles its Admin layout periodically — if that path has moved, search Admin for “Channel groups.” Verify live before you rely on any screenshot, including mine.)

1. Name the group something like “AI + Default” so you know at a glance what it is.
2. Add new channel, name it AI.
3. Set the condition: Source → matches regex → paste an anchored, domain-scoped pattern (see the Scripts tab — do not use the overly broad “any string containing ai” patterns floating around secondary summaries; they false-positive on domains like mail.com and wikipedia.org).
4. Drag the AI channel above Referral. This is the load-bearing step (next section).
5. Save.

Supported match fields, if you want to get fancy: Campaign ID, Campaign name, Default channel group, Manual ad content, Medium, Source, and Source platform. For a belt-and-suspenders setup, add a second condition matching utm_source containing chatgpt to also catch ChatGPT Search’s self-appended tag (more on that below).

Step 3 — get the channel order right (the silent failure mode)

This is the single most important sentence in the whole setup, straight from Google’s docs: “Traffic is included in the first channel whose definition it matches given the current order of channels in the group.” Read that again with AI traffic in mind. A session from chatgpt.com legitimately matches Referral (it’s a referring domain). So if Referral sits above your AI channel in the ordering, every single AI session gets claimed by Referral first and never reaches your AI channel.

There’s no error. No warning. No red flag in the UI. The report just quietly reads zero (or near-zero) AI traffic while your AI channel silently does nothing — and you’ll spend an afternoon debugging a regex that was fine all along. Drag AI above Referral, save, and confirm by checking that the AI row now has sessions in a Traffic acquisition report scoped to your custom group.

Step 4 — the part most guides skip: build an Exploration

A channel is a label. It tells you how much AI traffic you got. It does not tell you which pages got it or whether any of it converted — and that’s the part stakeholders actually care about. That lives in an Exploration.

Explore > Blank (Free Form). Then:

• Dimensions: add Session source / medium, Landing page + query stringThe `?key=value` data tacked onto the end of a URL after a question mark — used for tracking, sessions, filtering, sorting, and search — and one of the biggest sources of duplicate URLs and wasted crawling in SEO., and optionally Session default channel group (or your custom group). Drag Landing page into Rows and Session source/medium into a secondary row or a column.
• Metrics: add Sessions, Engagement rate, and — the one that matters — your Key events (conversions). Revenue too, if you have ecommerce or a value on your key events.
• Filter or segment to AI sources. You can add a filter (Session source/medium matches regex your AI domains), but the better move is to build a reusable segment (next section) so this view drops into any report, not just this one.

Now you have a table that answers real questions: which landing pages AI tools send traffic to, how engaged that traffic is, and what it converts.

Build the AI segment once, reuse it everywhere

In the Exploration’s Segments panel, + > Build a new segment > Session segment. Condition: Session source / medium matches regex with your AI pattern (and, if you want ChatGPT Search’s tagged traffic, an OR condition on utm_source containing chatgpt). Name it AI Sources. Now you can:

• Drop it into any Exploration alongside Organic Search, Paid, and Referral segments for side-by-side comparison.
• Compare AI’s engagement and conversion rate against your other channels in the same table — which is far more persuasive than quoting a conversion stat from someone else’s blog post.

A segment is more flexible than a channel because it isn’t bound to one report or one channel-group slot. Build both — the channel for at-a-glance reporting, the segment for analysis.

Step 5 — the landing-page-by-AI-source report (the most actionable one)

If you build one report from this article, build this. Landing page in Rows, your AI Sources segment applied, Sessions and Key events as metrics. What you get is a ranked list of the pages AI tools are actually driving people to — which is a usable proxy for which of your content is winning citations and retrieval in AI answers.

What to do with the output: double down on the page types that concentrate AI traffic. When Ahrefs ran this analysis on our own data, we foundA 302 (\"Found\") is a temporary redirect: it forwards users to a new URL while telling search engines the original URL should stay in the index. It's a weak canonicalization signal, not the zero-equity dead end of SEO folklore. that 80% of our AI search traffic went to our homepage, product pages, and free tools — not our blog posts. That’s exactly the kind of insight this report surfaces: it tells you where to invest (more free tools, stronger product pages) rather than guessing. Your concentration will differ, but the report type is the same.

Step 6 — conversion and revenue reporting for AI traffic

Session count is the vanity number; conversions are the one that gets budget. Apply your AI Sources segment to your standard key-event / conversion reports, or build the comparison directly in an Exploration with Sessions, Key events, and (if you have it) Revenue as metrics, segmented AI vs. Organic vs. Paid. The story that tends to land with stakeholders is conversion rate, not volume — AI traffic is frequently a small share of sessions that punches well above its weight on conversions, so a table that shows “AI is 1% of sessions but converts at Nx organic” reframes the whole conversation. (The specific conversion-premium figures — the 23x and Loamly’s 10.21% vs 2.46% numbers — are owned by the attribution siblingAI traffic attribution is the practice of correctly identifying and measuring website visits that come from AI tools — ChatGPT, Perplexity, Gemini, Claude, AI Overviews, and AI browsers. It's hard because many of those tools strip the referrer header, so the visits land in your analytics as Direct traffic with no source.; pull your own numbers from this report rather than quoting theirs.)

Step 7 — UTM tagging: platform-specific, not “AI strips everything”

The blanket claim you’ll read everywhere — “AI platforms strip all UTMs, so tagging is pointless” — is wrong in both directions. The reality in 2026:

• ChatGPT increasingly appends its own utm_source=chatgpt.com on some outbound links, notably from ChatGPT Search. This is the rare case of an AI platform making attribution easier — worth catching with a utm_source condition in your channel or segment. (Search Engine Roundtable reported OpenAI expanding this behavior; the page 403’d during research, but multiple secondary sources corroborate the direction.)
• Perplexity, Gemini, and Claude generally don’t add or preserve UTMs on cited links. No vendor documents its outbound-link behavior, so this is from independent testing, not official docs — treat it as “here’s what testing shows,” which is the honest framing for all of this.
• None of it helps with links you don’t control. When an AI tool cites you, it cites the canonical URLHow search engines pick one canonical URL among duplicates and consolidate signals onto it. it found — not some tagged URL you’d like it to use. You cannot UTM-tag your way into attribution for citations.

Where UTM tagging does still earn its keep: links you place yourself in your own outbound content (newsletters, syndication, citation-bait you publish elsewhere), where you control the URL and can tag it — provided the destination platform doesn’t scrub it. Marginal, but real. Just don’t expect it to solve the citation-attribution problem, because it structurally can’t.

Step 8 — combining with Search Console for AI-features context

Google’s Gen AI performance reports (June 3, 2026) surface your appearances in “AI Overviews, AI Mode, and generative AI features in Discover” — but impressions only: no clicks, no CTR, no position. So you can’t get “AI Overview clicks” from GSC any more than you can from GA4.

The practical workaround is a manual URL-level join, and it’s worth being blunt that it’s manual:

1. In Search ConsoleGoogle's free tool for monitoring crawling, indexing, and search performance. > Performance, filter by the AI-features search-appearance type and export the pages that appear (impressions).
2. In GA4, open your landing-page report (Step 5) and pull sessions/key events for those same URLs.
3. Join the two exports on landing-page URL — not on channel, because GA4 can’t isolate AI-feature clicks, so a channel join is impossible.

The output tells you which URLs are showing up in AI features (GSC impressions) and what those same URLs do in GA4 (sessions, conversions). If you’ve linked GA4 and GSC via Admin > Product links > Search Console links, some of this surfaces in GA4’s Search Console reports — but the AI-feature slice still requires the manual join because neither product tags sessions as “came from an AI Overview.” Set expectations accordingly: this is a workflow, not a button.

Cross-reference Bing Webmaster ToolsMicrosoft's free portal for monitoring and improving how a site appears in Bing search — the peer to Google Search Console, plus IndexNow instant indexing, richer backlink data, and keyword volumes. Because Bing's index also feeds Microsoft Copilot, it doubles as a window into AI-search visibility.’ AI Performance reportThe Google Search Console report that shows how your site actually performed in Google Search, built from real impressions and clicks. It reports four metrics — clicks, impressions, average CTR, and average position — and keeps the most recent 16 months of data. (public preview, Feb 2026) the same way — it exposes citations and the groundingGrounding is anchoring an AI model's answer to source documents it retrieves at the moment you ask — not to the patterns frozen into its weights during training. Retrieval-Augmented Generation (RAG) is the most common way to do it. queries Copilot searched to find you. Copilot’s referrer behavior is inconsistent (Copilot web passes one intermittently; the Windows app never does), so a GA4 regex under-counts Copilot no matter what — the Bing citation count is your cross-check.

Where this still falls short

Several honest limits, then hand off:

1. The 35–70% dark floor is untouched by everything above. You’re instrumenting the referred slice well; the referrer-less slice stays in Direct.
2. AI Overviews / AI Mode can’t be isolated — permanently merged into Organic Search by Google’s own channel definitions.
3. Longer-range reports run into retention, not just referrers. GA4’s event-level data retention (Admin > Data settings > Data retention) defaults to 2 months and tops out at 14 — an Exploration built on event-scoped data can’t look back further than that window, independent of anything AI-related. Your property’s start date is a second hard boundary: there’s no AI traffic to report before the property existed or before you started collecting. And in contexts where consent signals fall below GA4’s reporting thresholds, low-count rows — a thin AI-traffic segment is a prime candidate — get modeled or suppressed rather than shown as zero. Don’t read a missing row as “no AI traffic”; read it as “below the reporting threshold, or outside the retention window.”
4. Channel-group edits can change how a report reads, including for past dates. Renaming, reordering, or adding a rule to your custom channel group can change how already-collected sessions get classified the next time you pull a report, since custom groups are evaluated against current rules at query time. A mid-quarter regex edit can quietly shift a month-over-month AI comparison — note the date whenever you edit the group, the same discipline the regex change log below already asks for.
5. A conversion comparison from Step 6 is session-scoped counting, not multi-touch attribution credit. The Exploration technique in this article counts Sessions and Key events directly. GA4’s separate Attribution reports apply a chosen attribution model (data-driven by default) that can assign AI a different share of credit in journeys with more than one touchpoint. If you need AI’s multi-touch credit rather than its session-level volume, pull that number from Attribution, not from the Exploration technique in Steps 4–6.

For the full “why it’s dark and what to do about the Direct baseline,” see the AI traffic attributionAI traffic attribution is the practice of correctly identifying and measuring website visits that come from AI tools — ChatGPT, Perplexity, Gemini, Claude, AI Overviews, and AI browsers. It's hard because many of those tools strip the referrer header, so the visits land in your analytics as Direct traffic with no source. deep dive; for where GA4 sits inside the broader five-layer measurement approach, see the measurement and reporting hubAI search measurement and reporting is the practice of tracking and communicating how AI search features — AI Overviews, AI Mode, ChatGPT, Perplexity, Gemini, Copilot — affect a brand's visibility, traffic, and revenue. It exists because most AI-referred traffic and exposure is invisible in standard analytics.. This article is the config; those own the strategy.

AI summary

A condensed take on the Advanced version:

• Two layers. Native AI Assistant channel (Default Channel Group, added May 13, 2026 — automatic, referrer-only, not retroactive, narrower/unpublished source list) plus a custom channel group you build (broader coverage, works on historical data, costs one of 2 standard-property slots; 360 gets 5).
• First check: Reports > Acquisition > Traffic acquisition, Session default channel group — look for an “AI Assistant” row.
• Build: Admin > Data display > Channel groups > new group; channel named AI; Source matches regex on AI domains (anchored, not “any string with ai”).
• The load-bearing rule — channel order. GA4 assigns traffic to the first channel it matches, so AI must sit above Referral or every AI session gets silently absorbed into Referral with no error.
• Setup is step one. The payoff is a Free Form Exploration: Session source/medium × Landing page × Key events — and a reusable AI segment droppable into any report for side-by-side comparison vs. Organic/Paid.
• Most actionable report: landing-page-by-AI-source (proxy for which pages win citations/retrieval); conversion/revenue reporting reframes AI from a small session share to a high-converting one.
• UTMs are platform-specific: ChatGPT increasingly appends utm_source=chatgpt.com; Perplexity/Gemini/Claude generally don’t; none of it tags links you don’t control.
• GSCA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. combine = manual URL join (GSC AI-feature impressions × GA4 sessions on the same landing page); GA4 can’t isolate AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. from Organic Search.
• Scope matters. Build reports on Session source/medium (session-scoped — “did this visit come from AI”) not First user source/medium (user-scoped — “was this user’s first-ever touch AI”). They answer different questions.
• Hard floor: 35–70% of AI visits arrive with no referrer and stay in Direct — everything here measures the referred slice only.
• Other limits: event-data retention (2–14 months) and property start date bound how far back an Exploration can look; consent-based thresholding can suppress a thin AI segment’s rows; custom channel-group edits can re-classify past sessions on next read, so log the date when you change one; and a session-scoped conversion comparison isn’t the same number as GA4’s model-based Attribution reports.

Official documentation

Primary-source documentation for configuring GA4 and reading AI-feature data.

Google Analytics

• What’s new in Analytics — AI Assistant channel — the May 13, 2026 entry announcing the AI Assistant Default Channel Group channel.
• Default Channel Group definitions — the authoritative per-channel rule table, including the AI Assistants channel and the Direct channel’s “no signal” definition.
• Create, edit, and apply custom channel groups — the mechanics doc: adding channels, match conditions, the first-match ordering rule, and property limits (2 custom groups on standard, 5 on 360).
• Analyze data with Explorations — the Explore workspace, Free Form technique, dimensions, metrics, and segments.
• Traffic-source dimensions, manual tagging, and auto-tagging — the session-scoped vs. first-user (user-scoped) distinction behind the report-building note above.
• Data retention — event-level retention windows (2–14 months) that bound how far back an Exploration can look.
• Get started with attribution — how GA4’s Attribution reports assign model-based credit, as distinct from the session-scoped counting this article’s Explorations use.

Google Search (for the GSCA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. join)

• Gen AI performance reports (June 3, 2026) — AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index., AI Mode, and generative-AI Discover appearances, impressions only.
• AI features and your website — how Google’s AI features surface your content.

Bing / Microsoft

• Introducing AI Performance in Bing Webmaster Tools (public preview) — total citations, average cited pages, and the groundingGrounding is anchoring an AI model's answer to source documents it retrieves at the moment you ask — not to the patterns frozen into its weights during training. Retrieval-Augmented Generation (RAG) is the most common way to do it. queries Copilot used to find you.

Quotes from the source

On-the-record statements relevant to configuring GA4 for AI trafficGA4 for AI traffic is the practical configuration work — native AI Assistant channel, a custom channel group with a source regex, Explorations, and a Search Console join — that lets you identify, segment, and report on the visits arriving from AI chatbots that GA4 can actually see.. Each link is a deep link that jumps to the quoted passage where the page allows it.

Google — the native AI Assistant channel

• “You can now identify how users are discovering your site through chatbots like ChatGPT, Gemini, and Claude via a new AI Assistant channel in your Default Channel Group reports.” — GA4 “What’s new,” May 13, 2026. Jump to quote

Google — the AI Assistants channel definition

• “AI Assistants is the channel by which users arrive at your site from sources like ChatGPT, Gemini, Deepseek, Copilot, or Grok.” — GA4 Default Channel Group definitions. Read the definition

Google — the Direct channel (why referrer-less AI lands here)

• “Direct is the channel by which users arrive at your site/app via a saved link or by entering your URL.” Its rule requires source (direct) and medium (not set) or (none) — i.e., no signal at all. — GA4 Default Channel Group definitions. Read the definition

Google — the channel-ordering rule (the load-bearing sentence)

• “Traffic is included in the first channel whose definition it matches given the current order of channels in the group.” — GA4 custom channel groups doc. This is why the AI channel must sit above Referral. Read the doc

Google — Search ConsoleA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. Gen AI reports (impressions only)

• The June 2026 Gen AI performance reportsThe Google Search Console report that shows how your site actually performed in Google Search, built from real impressions and clicks. It reports four metrics — clicks, impressions, average CTR, and average position — and keeps the most recent 16 months of data. cover “AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index., AI Mode, and generative AI features in Discover” — impressions only, with no clicks, CTR, or position. — Google Search Central blog. Read the announcement

Patrick Stox, Ahrefs — why so much AI traffic lands in Direct

• “Websites have control over what info they send. They can send the full path, just the origin, or nothing — it’s up to them. We report whatever referrer we’re told to report. If they don’t send us one, then it would go in the ‘Direct’ bucket.” — from my write-up on AI assistants breaking web analytics. Read the post

Which AI-traffic setup do you need?

Work down from what you have today to the right next configuration step.

SOP: set up AI-traffic tracking in a GA4 property

A repeatable procedure for standing this up on one property (or the same steps per client). Budget ~20 minutes the first time.

1. Establish the baseline. Reports > Acquisition > Traffic acquisition → primary dimension Session default channel group → note whether an AI Assistant row exists and its current session count.
2. Create the custom channel group. Admin > Data display > Channel groups > Create new channel group. Name it “AI + Default.”
3. Add the AI channel. Add new channel → name AI → condition Source matches regex → paste your anchored AI-domain pattern (Scripts tab). Optionally add an OR condition: Manual term / utm_source contains chatgpt to catch ChatGPT Search’s tag.
4. Order it. Drag the AI channel above Referral. Save.
5. Verify the order worked. Open a Traffic acquisition report scoped to the new group; confirm the AI row now shows sessions (not zero). If it’s zero and you know you have AI referrals, re-check the ordering first, the regex second.
6. Build the reusable AI segment. Explore > Blank > Segments > + > Session segment → Session source / medium matches regex (same pattern) → name it AI Sources.
7. Build the landing-page Exploration. Free Form → Rows: Landing page + query string → Metrics: Sessions, Engagement rate, Key events → apply the AI Sources segment. Save it.
8. Add the conversion comparison. Duplicate the Exploration; add Organic Search and Paid segments alongside AI Sources; compare Key events and conversion rate side by side. This is your stakeholder view.
9. Set up the GSCA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. cross-reference. Admin > Product links > Search ConsoleGoogle's free tool for monitoring crawling, indexing, and search performance. links (link if not already). Establish the monthly manual join: export GSC AI-feature impression pages, match to GA4 landing-page sessions/conversions on the same URLs.
10. Document the floor. In whatever report you share, add a one-line caveat that 35–70% of AI traffic is referrer-less and invisible here, so these are minimums.

Recurring maintenance (quarterly): re-check the regex against newly prominent AI platforms, confirm GA4’s Admin paths haven’t moved, and re-verify the channel order survived any channel-group edits.

What not to do

The recurring mistakes that make GA4 AI tracking misleading — each with why it’s wrong and what to do instead.

1. “GA4 tracks all AI traffic automatically since the May 2026 update.” Why it’s wrong: the native AI Assistant channel only catches sessions that arrive with a recognized referrer. The 35–70% dark-traffic floor is completely untouched by the update, and the recognized-referrer list is narrower and not fully published. Do instead: treat the native channel as a floor-of-a-floor, watch your Direct baseline as the real diagnostic, and never report the AI Assistant number as “our AI traffic” without the caveat.

2. Leaving the AI channel below Referral. Why it’s wrong: GA4 stops at the first matching channel. chatgpt.com is a valid referral, so an AI channel placed below Referral catches nothing — silently, with no error. You’ll think your regex is broken. Do instead: drag AI above Referral and verify the AI row has sessions before trusting the report.

3. Using an over-broad regex like “any string containing ai.” Why it’s wrong: patterns that match any substring ai false-positive on mail.com, wikipedia.org, retail.com, and dozens more, inflating your AI number with non-AI traffic. Do instead: use anchored, domain-scoped alternation (chatgpt\.com|perplexity\.ai|…) — see the Scripts tab. Verify it in the live GA4 UI before publishing it to a client.

4. Stopping at the channel group and calling it done. Why it’s wrong: a channel is a label with no analysis behind it. It tells you how much AI traffic arrived but not which pages got it or whether it converted — the questions that actually drive decisions. Do instead: build the landing-page Exploration and the conversion comparison. Setup is step one, not the finish line.

5. Assuming “AI platforms strip all UTMs, so tagging is pointless.” Why it’s wrong: it’s platform-specific. ChatGPT increasingly appends its own utm_source=chatgpt.com; Perplexity, Gemini, and Claude generally don’t add UTMs; and none of it applies to links you don’t control (AI cites your canonical URLHow search engines pick one canonical URL among duplicates and consolidate signals onto it., not a tagged one). Do instead: add a utm_source contains chatgpt condition to catch the tagged traffic, and tag only the outbound links you actually control.

6. Expecting GA4 to filter to “traffic from AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index..” Why it’s wrong: AI Overview and AI Mode clicks are permanently merged into Organic Search by Google’s own channel definitions — the referrer is indistinguishable from a normal Google click, so no regex or custom channel can separate them. Do instead: accept the boundary; use the manual GSCA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results.-impressions × GA4-sessions join on landing-page URL to get some AI-features context.

GA4 AI-traffic setup checklist

A pass to confirm your AI tracking is configured and actually reporting:

• Checked Traffic acquisition (Session default channel group) for a native AI Assistant row and noted the baseline.
• Created a custom channel group with an AI channel (Source matches regex).
• Regex is anchored and domain-scoped — no “any string containing ai” patterns that false-positive on mail.com / wikipedia.org.
• The AI channel sits above Referral in the channel order.
• Verified the AI row shows sessions (not zero) after fixing the order.
• Optional: added a utm_source contains chatgpt condition to catch ChatGPT Search’s self-appended tag.
• Built a reusable AI Sources segment (not just a channel).
• Built a landing-page × AI-source Exploration (Landing page + Session source/medium × Sessions + Key events).
• Built the conversion comparison (AI vs. Organic vs. Paid, key events + conversion rate).
• Linked GSCA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. (Admin > Product links) and established the manual AI-feature impressions × GA4 sessions join on landing-page URL.
• Cross-checked Bing Webmaster ToolsMicrosoft's free portal for monitoring and improving how a site appears in Bing search — the peer to Google Search Console, plus IndexNow instant indexing, richer backlink data, and keyword volumes. Because Bing's index also feeds Microsoft Copilot, it doubles as a window into AI-search visibility. AI Performance citations for Copilot (which under-counts in a GA4 regex).
• Documented the 35–70% dark-traffic floor caveat on any shared report.
• Confirmed you’re not claiming to isolate AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. (merged into Organic).

GA4 AI-traffic cheat sheet

The two layers

Menu paths (verify live — GA4 Admin shifts)

The rule that breaks setups

• GA4 assigns each session to the first channel it matches → AI must sit above Referral, or AI sessions are silently absorbed into Referral.

UTM behavior by platform

Fast facts

• Custom channel groups: 2 on standard properties, 5 on GA4 360; 50 channels per group.
• GSC Gen AI reports = impressions only (no clicks/CTR/position).
• AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. / AI Mode = merged into Organic Search, not separable in GA4.
• Dark-traffic floor: 35–70% of AI visits arrive referrer-less → Direct.

The regex (anchored, not broad)

The AI channel’s condition is Source matches regex. Do not reproduce the loose “any string containing ai” patterns that circulate in secondary summaries — they false-positive on mail.com, wikipedia.org, retail.com, and more. Anchor to actual domains with escaped dots and alternation.

Minimal, high-signal (the platforms that actually send traffic):

(chatgpt\.com|chat\.openai\.com|perplexity\.ai|claude\.ai|gemini\.google\.com)

Fuller coverage (add the long tail as they grow):

chatgpt\.com|chat\.openai\.com|perplexity\.ai|claude\.ai|gemini\.google\.com|copilot\.microsoft\.com|deepseek\.com|grok\.com|x\.ai|meta\.ai|chat\.mistral\.ai|you\.com|phind\.com|poe\.com|pi\.ai

Always verify the pattern against your own Referrals report first — check Reports > Acquisition > Traffic acquisition, add Session source as a secondary dimension, and see which AI hostnames actually appear in your data before hard-coding a list. Then confirm the pattern behaves in GA4’s live channel-group UI (the field’s regex flavor and case handling can surprise you).

Test cases before you save the pattern. This list is dated to 2026-07-18 — AI platforms launch and rename often, so re-derive it from your own Referrals report rather than trusting any static list forever:

Run each row through GA4’s channel-group UI (or a regex tester using the same flavor) before saving — a pattern that passes your read-through but fails one of these rows will misclassify live traffic.

Keep a change log. Every time you add, remove, or re-anchor a domain in the pattern, note the date and what changed next to your channel-group documentation. New AI platforms appear and some fold or rebrand; a dated log is what lets you (or whoever inherits this property) tell “AI traffic dropped” from “we stopped matching a domain that renamed itself” months later. It’s the same discipline the Advanced lens’s “Where this still falls short” section asks for when you edit the channel group itself.

See the referrer an AI click actually sent — Chrome DevTools Console

Attribution problems are usually referrer problems. To see exactly what a real click from an AI tool handed your page, click through from the AI answer to your site, open DevTools > Console, and run:

// What referrer did this navigation carry?
console.log("referrer:", document.referrer || "(empty — no referrer sent)");

// Any UTM tags on the landing URL? (catches ChatGPT's utm_source=chatgpt.com)
console.log(
  "utm params:",
  Object.fromEntries(new URLSearchParams(location.search).entries())
);

An empty document.referrer is the dark-traffic case in miniature: that visit will land in Direct no matter what channel group you build. A populated utm_source (often chatgpt.com) is the case your utm_source channel condition catches.

A bookmarklet to check referrer + UTMs on any page

Drop this into a bookmark’s URL field; click it after arriving from an AI tool to get a one-glance readout without opening DevTools:

javascript:(function(){var r=document.referrer||"(empty)";var u=location.search||"(none)";alert("Referrer:\n"+r+"\n\nQuery/UTMs:\n"+u);})();

Extract AI-referrer hostnames from your GA4 export (shell)

If you export a Traffic acquisition report (or query the GA4 Data API), this pulls the distinct source hostnames that look like AI platforms so you can build a data-driven regex instead of guessing:

# sources.csv: one Session source per line (from a GA4 export)
grep -Ei 'chatgpt|openai|perplexity|claude|gemini|copilot|deepseek|grok|meta\.ai|mistral|you\.com|phind|poe|pi\.ai' sources.csv \
  | sort -u

Feed the deduped list back into the alternation pattern above — that way your regex matches what’s genuinely in your data, escaped-dot by escaped-dot.

Tools for measuring AI traffic

• GA4 — Reports > Acquisition > Traffic acquisition — the native AI Assistant channel baseline and your custom-channel-group view.
• GA4 — Explore (Explorations) — Free Form reports for landing-page × AI-source and conversion cross-tabs; where the real analysis happens.
• GA4 — Admin > Channel groups — build and order your custom AI channel (mind the above-Referral rule).
• Google Search ConsoleA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. — Performance (Gen AI reports) — AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. / AI Mode / Discover impressions to join against GA4 landing pages (impressions only).
• Bing Webmaster ToolsMicrosoft's free portal for monitoring and improving how a site appears in Bing search — the peer to Google Search Console, plus IndexNow instant indexing, richer backlink data, and keyword volumes. Because Bing's index also feeds Microsoft Copilot, it doubles as a window into AI-search visibility. — AI Performance reportThe Google Search Console report that shows how your site actually performed in Google Search, built from real impressions and clicks. It reports four metrics — clicks, impressions, average CTR, and average position — and keeps the most recent 16 months of data. — Copilot citations and groundingGrounding is anchoring an AI model's answer to source documents it retrieves at the moment you ask — not to the patterns frozen into its weights during training. Retrieval-Augmented Generation (RAG) is the most common way to do it. queries; the cross-check for Copilot traffic a GA4 regex under-counts.
• Ahrefs Web Analytics — a purpose-built alternative with its own AI channel, if you want a second read that isn’t dependent on GA4’s channel model. Same underlying dark-traffic limit applies to any analytics tool.
• Chrome DevTools Console — inspect document.referrer and the landing URL’s UTMs on a real AI click (see Scripts).

Verify AI-source classification before publishing a report

Test to run: Use a tagged test link or a controlled referrer fixture that matches each custom channel rule, then inspect the resulting source/medium and channel in GA4. Expected result: Recognized AI sources enter the intended custom channel without swallowing unrelated referral or organic sessions. Failure interpretation: A regular expression is too broad, too narrow, or evaluated in the wrong channel-rule order. Monitoring window: After GA4 processes the test event. Rollback trigger: The rule reclassifies a material set of known non-AI sources.

Verify report totals reconcile

Test to run: Compare the custom AI channel report with an exploration filtered by the same source/medium definitions and review a sample of underlying sources. Expected result: The same defined referred sessions appear in both views, with differences explained by report scope, date, or processing. Failure interpretation: Filters, attribution settings, or channel definitions do not match. Monitoring window: After the selected reporting period has processed. Rollback trigger: The new report cannot be reconciled or removes established historical channel context.

Resources worth your time

My related writing

• How to Track and Analyze Your AI Traffic — my/Ahrefs’ walkthrough of setting up AI-traffic tracking, including channel-group and reporting steps.
• AI Assistants Are Breaking Web Analytics and Hurting Their Future — the per-platform referrer testing behind why so much AI traffic lands in Direct.
• Google Made It So You Can’t Track Clicks From AI Mode (Partially Fixed) — the noreferrer behavior I reported, and why Google’s own AI can’t be isolated in GA4.
• 80% of Our AI Search Traffic Goes to Our Homepage, Product Pages, and Free Tools — a worked example of exactly the landing-page-by-AI-source insight this article teaches you to build.

My speaking

• How Search Works (SlideShare) — my walkthrough of crawlingCrawling is how search engines use automated bots (like Googlebot and Bingbot) to discover URLs and download pages. A page has to be crawlable to be indexed, but crawling on its own isn't a ranking factor., renderingTurning HTML, CSS, and JavaScript into the final visual page and DOM., indexingStoring a crawled page in the search index so it can appear in results. Crawled is not the same as indexed — Google selects what to keep, and indexing isn't guaranteed., and ranking, for context on where AI-search measurement fits. (My standing disclaimer applies: “This is my understanding of systems… not going to be 100% complete or accurate.”)

Official

• GA4 — What’s new (AI Assistant channel) and Custom channel groups.
• Google Search Central — Gen AI performance reports.

From around the industry

• Google Analytics Adds AI Assistant As Default Channel Group (Search Engine Journal) — coverage of the May 13, 2026 rollout.
• How to Track AI Traffic in GA4 (Orbit Media, Andy Crestodina) — a solid practitioner walkthrough of the channel-group approach.
• Tracking AI Traffic in GA4: A Step-by-Step Guide (Two Octobers) — step-by-step channel-group setup.
• How to Track AI and LLM Chatbot Traffic in GA4 (Tripledart) — another configuration reference.
• AI Traffic in Google Analytics 4 (Analytics Mania) — channel-group setup (stops before Explorations/conversions, which is where this article picks up).
• The AI Traffic Attribution Crisis (Loamly) — the 446,405-visit study behind the 70.6% referrer-less figure.
• r/GoogleAnalytics — community debugging for channel groups and Explorations.

Stats worth citing

• 35–70% of AI visits arrive with no referrer and land in Direct — the hard floor every GA4 configuration runs into. The 70.6% high end comes from Loamly’s 446,405-visit sample. Source
• 80% of Ahrefs’ AI searchAI search uses large language models and retrieval-augmented generation (RAG) to synthesize an answer from multiple sources rather than returning a ranked list of links. Examples include Google AI Overviews, ChatGPT Search, and Perplexity. traffic went to the homepage, product pages, and free tools — a worked example of what a landing-page-by-AI-source report surfaces (page- type concentration you can act on). Source
• Native AI Assistant channel added May 13, 2026 to GA4’s Default Channel Group — automatic, referrer-based, and not retroactive. Source
• Custom channel group limits: 2 on standard GA4 properties, 5 on GA4 360, up to 50 channels each — the budget you’re spending when you build an AI channel. Source
• GSCA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results. Gen AI reports are impressions-only (no clicks, CTR, or position), which is why combining with GA4 is a manual URL-level join rather than a native report. Source

Test yourself: GA4 for AI Traffic

Five quick questions on configuring GA4 to see AI traffic. Pick an answer for each, then check.

GA4 for AI Traffic

GA4 for AI traffic is the practical configuration work — native AI Assistant channel, a custom channel group with a source regex, Explorations, and a Search Console join — that lets you identify, segment, and report on the visits arriving from AI chatbots that GA4 can actually see.

Related: AI Traffic Attribution, Measurement and Reporting, LLM Visibility

GA4 for AI Traffic

GA4 for AI traffic is the hands-on setup inside Google Analytics 4 that turns “AI is sending us visits” into a report you can act on. It has two layers. The first is GA4’s native AI Assistant channel, added to the Default Channel Group on May 13, 2026, which automatically buckets sessions that arrive with a recognized AI referrer (ChatGPT, Gemini, Claude, Copilot, Deepseek, Grok, and others). The second is a custom channel group you build yourself — a channel named for AI whose condition is Source matches regex against the AI platform domains — which gives you broader coverage and lets you re-segment historical data the native channel can’t touch (it isn’t retroactive).

Configuration is only half the job. The channel is a label; the analysis is a GA4 Exploration — a Free Form report that cross-tabs Session source/medium against Landing page and key events so you can see which pages AI tools send traffic to and whether that traffic converts. Building the AI view as a reusable segment (rather than only a channel) lets you drop it into any report and compare it side by side against Organic Search or Paid.

Two hard limits define the ceiling. Because 35–70% of AI visits arrive with no referrer, they land in Direct by construction and never reach either the native channel or your custom one — no regex fixes that. And Google’s AI OverviewsAI Overviews are the AI-generated summary box Google shows above or within its regular search results, written by Gemini models from pages retrieved out of Google's normal Search index. It's a Search feature, not a separate platform or index. and AI Mode clicks are classified as regular Organic Search in GA4, so you cannot isolate them there; the workaround is a manual URL-level join with Search ConsoleA free Google service that reports how a site performs in Google Search and surfaces problems with how Google crawls, indexes, and serves it. It's first-party data straight from Google — but you don't need it to appear in results.’s Gen AI performance data (impressions only). GA4 for AI traffic is about instrumenting the traffic you can see well, while knowing what it can’t show you.

Related: AI Traffic Attribution, Measurement and Reporting, LLM Visibility

Changelog