Last Updated: July 2, 2025

What is AI traffic in GA4?

AI traffic in GA4 refers to user interactions initiated or influenced by AI-driven applications or systems.

These applications or systems could be chatbots, virtual assistants, automated testing tools, or any software that uses AI to interact with web pages, apps, or services.

For example, if a user accesses your website by clicking a link generated by Perplexity AI in a normal browsing session, this would be considered AI traffic.

Why is understanding and analysing AI traffic crucial?

1. You can personalise users’ experiences by analysing the impact of AI on user preferences.
2. You can improve user journeys by identifying issues and trends in AI interactions.
3. Target ads more effectively with insights from AI-driven traffic data.
4. Assess and enhance AI’s effectiveness in attracting engaged visitors.
5. Anticipate trends to innovate and stay competitive in evolving markets.

By harnessing the power of AI traffic analysis, businesses can unlock a deeper understanding of their users, optimise their offerings, and make data-driven decisions for a thriving online presence.

Overview of AI traffic analysis reports in GA4.

To conduct AI traffic analysis in GA4, we will create a new exploration report from scratch. This new report would have nine tabs. 

Each tab displays a sub-report that measures the performance of your AI traffic.

The following are the nine sub-reports we would create in our exploration report:

#1 Overview – This report provides an overview of each AI traffic source:

#2 Landing Pages – Use this report to measure the performance of landing pages from AI traffic:

#3 Devices – Use this report to measure the performance of different devices (desktop, mobile, smart TV, tablet) which sent AI traffic to your website:

#4 Browsers – Use this report to measure the performance of different web browsers which sent AI traffic to your website:

#5 Countries – Use this report to determine the countries which sent AI traffic to your website:

#6 Conversions – Use this report to determine all the conversions (key events) generated by AI traffic on your website:

#7 ECommerce – Use this report to measure the ecommerce performance of AI traffic to your website:

#8 User Flow – Use this report to determine how the AI traffic is using your website:

#9 Funnel – Use this report to determine how AI traffic is converting on your website:

How to create the AI traffic reports in GA4?

Follow the steps below to create the AI traffic tracking report in GA4:

Step-1: Login to your GA4 property.

Step-2: Click on Explore from the left-hand side menu:

Step-3: Scroll down and navigate to the report named ‘Organic Search Traffic Analysis‘:

Note: If you do not already have this report, then stop reading this article for now and create this report first. We will use this report as a template to create a new report. Follow the instructions in this article: Organic Search Traffic Analysis in GA4 – Complete Guide.

Step-4: Click on the three dots menu next to the ‘Organic Search Traffic Analysis’ report and then click on the ‘Duplicate‘ option from the drop-down menu:

Step-5: Click on ‘Copy of [Organic Search Traffic Analysis]‘ to open the report:

Step-6: Rename the report to [Advanced AI Traffic Analysis]:

Step-7: Hover your mouse over the ‘Organic Search‘ segment and then click on the three dots menu next to it:

Step-8: Click on the ‘Remove‘ option from the drop-down menu:

Step-9: Click on the ‘Remove Segment‘ button:

Step-10: Click on the + button next to SEGMENTS to add a new segment:

Step-11: Click on ‘Event Segment’:

Step-12: Define your segment like the one below and then click on the ‘Save and Apply’ button:

Segment Name: AI Traffic

Include events when: 

Page referrer matches regex ^.*\.ai/.*|.*\.openai.*|.*copilot.*|.*chatgpt.*|.*gemini.*$

You should now see your new segment listed under the ‘SEGMENTS’ column:

Step-13: Make sure that you are looking at the report under the ‘Overview’ tab:

Step-14: Hover your mouse over the dimension ‘First user source / medium‘ and then click on the cross button next to it to delete it from the canvas on the right:

You should now see a screen like the one below:

Step-15: Import the dimension ‘Page referrer’ to the report:

Step-16: Double-click on the dimension ‘Page referrer’ so that it is automatically added to the canvas on the right:

The AI traffic overview report would look like the one below:

Step-17: Click on the ‘Landing page’ tab:

Step-18: Hover your mouse over the ‘AI Traffic’ segment to display the three dots menu:

Step-19: Click on the ‘Apply’ button from the drop-down menu:

You should now see the ‘Landing Pages’ report for the AI traffic like the one below:

Step-20: Click on the remaining 7 tabs of your exploration report one by one and then apply the ‘AI traffic’ segment to them as described earlier.

That’s how you can create various reports to track AI traffic in GA4.

Introduction to AI Traffic Channel Group.

Since AI chatbots are becoming significant website traffic sources, grouping AI-referred traffic into a single channel has become very important.

AI traffic in GA4 is currently categorised under “referral” via dozens of different referrers. A custom channel group helps separate this unique traffic type for better data analysis.

An AI Traffic channel group in GA4 can be used as primary or secondary dimensions in reports and for creating audience conditions, allowing for a more detailed and flexible analysis of AI-referred traffic.

The channel group can also be applied retroactively.

When you create a new channel group for AI traffic in GA4, it will automatically be applied to all historical data in your GA4 property.

This means you can immediately analyse past AI-referred traffic without waiting for new data to accumulate.

Creating an AI Traffic Channel Group in GA4.

Follow the steps below to create a new AI Traffic Channel group in GA4:

Step-1: Navigate to GA4 Admin > Data Display > Channel groups.

Step-2: Click on the three dots menu next to the default channel group and then click on ‘Copy to create new‘.

Step-3: Rename your new channel group and update the description:

Step-4: Click on the ‘Add new channel‘ button.

Step-5: Name the new channel ‘AI Traffic‘.

Step-6: Click on the ‘Add condition group‘ button and then add the following condition to define your new custom channel:

Source matches regex ^.ai|..openai.|.copilot.|.chatgpt.|.gemini.|.gpt.|.neeva.|.writesonic.|.nimble.|.outrider.|.perplexity.|.google.bard.|.bard.google.|.bard.|.edgeservices.|.gemini.google.$

Step-7: Click on the ‘Save Channel‘ button.

Step-8: Click on the ‘Reorder‘ button and then drag the AI traffic channel just above the ‘Referral’ channel.

By placing the AI traffic channel above the referral channel, you ensure that AI traffic is correctly attributed before being potentially miscategorized as general referral traffic.

Step-9: Click on the ‘Apply‘ button and then on the ‘Save group‘ button.

Step-10: Navigate to Reports > Acquisition > Traffic acquisition.

Step-11: Scroll down to the data table and then change the primary dimension to the new channel group you created earlier.

Step-12: If your GA4 property is recording traffic from AI websites, you should see AI traffic being reported via the ‘AI traffic’ channel:

Step-13: Type ‘AI traffic‘ in the search box and press the enter key to filter out the AI traffic channel group.

Step-14: Add a secondary dimension to the data table named ‘Session source/medium‘.

You should now see a data table like the one below:

 Related Article: Tracking AI Traffic in GA4 BigQuery.

Caveat: Vet your referrer data before including it in your data analysis.

So this is not traffic from chatgpt but BOT traffic, which is easier to spot: 0 engaged sessions, 0% engagement rate and 0 seconds average engagement time per session.

Legitimate traffic from ChatGPT typically has “referral” as the medium.

The (not set) value often indicates malformed tracking data, which bots frequently generate.

This is a solid reminder to thoroughly “vet” referrer data before including it in data analysis.

How AI Traffic should be analysed in GA4?

AI traffic should be analysed in GA4 primarily at the session level rather than the user level.

AI visits are typically stateless and do not represent persistent or identifiable users.

Each AI-driven interaction is typically treated as a new session, often originating from referral sources such as “perplexity. ai,” or “gemini. google. com.”

Because these interactions lack continuity and user identification, AI traffic should be analysed in GA4 primarily at the session level rather than the user level.

AI Traffic in GA4 often seems to be more engaged.

AI chatbots mimic human interactions on websites, generating non-human traffic often mistaken for real users.

Their visits exhibit patterns such as long sessions, rapid page loads, and unusual navigation paths. Analysing server logs, GA4, and BigQuery can detect them.

Despite high engagement, AI-driven traffic often yields low conversions, impacting marketing effectiveness.

For more details: Why AI Chatbot Traffic is More Engaged in GA4.