Home / How to Track AI Chatbot Traffic in GA4

How to Track AI Chatbot Traffic in GA4

Learn how to track AI chatbot traffic in GA4 with our step-by-step guide. Optimize your strategy with actionable insights from AI-driven sessions.

Key Takeaways:

  • AI platforms should be treated as a traffic source, just like organic search, paid traffic, referrals, etc.
  • In a GA4 Exploration, view sessions by page referrer and apply a filter with “Match regex” to filter sessions by AI traffic source:
    ^https:\/\/(www\.meta\.ai|www\.perplexity\.ai|chat\.openai\.com|claude\.ai|chat\.mistral\.ai|gemini\.google\.com|bard\.google\.com|chatgpt\.com|copilot\.microsoft\.com)(\/.*)?$
  • This tracking method only tracks clicks from AI platforms, not actual AI bot visits to your website

The rapid rise of AI chatbots like ChatGPT, Bard, and Perplexity means more users are interacting with websites via these platforms. But how do you track these interactions? Thankfully, we’ve learned how to track traffic from AI chatbots using Google Analytics 4 (GA4). In this guide, we’ll walk you through the tracking setup process, what the data means, and the importance of these metrics for making data-driven decisions.

Why Track AI Chatbot Traffic?

As every website owner knows, it’s important to track user behavior across your site — but it’s also important to know how users made it to your site in the first place. With AI-powered conversations on the rise, you have to treat these platforms like another traffic source. 

Tracking AI chatbot traffic provides insight into how your site is being discovered through these new channels, allowing you to:

  • Understand where users are coming from in AI conversations.
  • Adjust your content strategy based on which AI tools are driving the most traffic.
  • Identify trends in user behavior and interests coming from these platforms.

Here’s how to set up tracking for your AI-driven referral traffic.

Step-by-Step Guide: Tracking AI Chatbot Traffic in GA4

Step 1: Log in to GA4 and Access Explorations

To start tracking AI traffic, head over to your GA4 dashboard and navigate to the Explorations section. This is where you can build a custom report tailored to tracking referrals from AI bots.

Step 2: Create a New Exploration

Click on the Blank template to create a new exploration. Give your exploration a descriptive name, like “AI Chatbot Traffic.”

Step 3: Add Your Dimensions and Metrics

For tracking AI chatbot traffic, you’ll need to set the right dimensions and metrics:

  • Sessions: This will be your primary metric for tracking the number of sessions generated by users clicking through from AI platforms.
  • Page Referrer: Add this dimension to capture the referral source (e.g., ChatGPT, Bard, Perplexity).

Step 4: Apply a Custom Regex Filter

To filter out relevant traffic from AI chatbots, you’ll need to apply a custom regex filter. This will capture sessions that come from the AI chatbot domains. Under filters, choose “Page referrer” and select “Matches regex.” Here’s the regex we used:

^https:\/\/(www\.meta\.ai|www\.perplexity\.ai|chat\.openai\.com|claude\.ai|chat\.mistral\.ai|gemini\.google\.com|bard\.google\.com|chatgpt\.com|copilot\.microsoft\.com)(\/.*)?$

This regex captures traffic from: 

  • Meta AI (www.meta.ai)
  • Perplexity AI (www.perplexity.ai)
  • OpenAI / ChatGPT (chat.openai.com)
  • Claude (claude.ai)
  • Mistral (chat.mistral.ai)
  • Gemini AI (gemini.google.com)
  • Bard AI (bard.google.com)
  • ChatGPT (chatgpt.com)
  • Microsoft Copilot (copilot.microsoft.com)

Step 5: Customize Your Report View


Now that you’ve set the dimensions and filter, customize the layout to make the data easier to analyze. For example:

  • Use a time-series chart to track AI-driven traffic over time.
  • Add a table view to break down traffic by source (e.g., ChatGPT, Bard).

Note that GA4’s Explorations default view will only provide you with data from the previous 2 months. You can update your data retention range to 14 months, but this may still be limiting if you’d like to go back further. 

Instead, try setting up a Looker Studio dashboard with a similar setup of sessions by page referrer with the regex filter applied. This will not only remove any time limitations but let you better customize your reporting.

Step 6: Analyze the Results

Once the exploration is set up, you should start seeing traffic data from AI chatbot sources. 

Review the trends to understand:

  • Which platforms are driving the most traffic.
  • Whether AI referrals contribute significantly to your overall sessions.
  • Patterns in user engagement from AI-driven sessions, such as where the users went internally after arriving from the AI chatbot, how long they spent on the site, how many pages they viewed, if they performed any event actions, etc. 

Important: If your exploration report is blank, your site may simply not have any traffic from AI chatbots either at all or within the 2-month timeframe. Try setting up a Looker Studio chart with a wider date range to see if any data appears.

Importance and Limitations

Tracking AI chatbot traffic in GA4 gives you valuable insights, but there are a few limitations to keep in mind:

1. Bot Traffic is Filtered

GA4 does not track visits from bots themselves. It only tracks clicks from human users engaging within the AI platforms.

2. New AI Bots

The regex filter only captures a handful of the top-known AI platforms, so you’ll need to update it as new AI services emerge.

Despite these limitations, the ability to track AI traffic is a powerful tool for understanding how emerging technologies are affecting your site’s performance.

Our Results So Far

Setting up your data exploration or Looker Studio dashboard is only the first step. The important thing is how you use the data once you have it. 

For instance, in 2024, GPO has seen: 

  • ChatGPT has generated over 38% of our AI chatbot traffic, with Perplexity AI a close second at 33%. 
  • Users who visited GPO’s Local Pages from chatbot services this year had a 36% engagement rate — more than double the rate of our second-highest traffic channel (17.5%).
  • Visitors spent an average of over 1.5 minutes on our sites compared to an average 51 seconds for all other traffic channels. 
  • Users from AI platforms performed at least 3 or more events and viewed two or more pages on average.

This data helps us optimize our content strategy for AI-driven sessions. For instance, we can analyze the event actions, review user experience on the pages viewed, and drill down on actions taken before exiting the site ensuring we’re meeting the needs of users arriving via these platforms.

Make Data-Driven Decisions with GPO

Data-driven decisions are essential for effective content strategies, and at GPO, we leverage a wide range of metrics to optimize performance. We stay at the forefront of reporting and analytics trends, using those insights to shape our clients’ strategies. Every blog, SEO recommendation, and local landing page we create is rooted in detailed research and backed by actionable traffic data.
Chat with our experts today to learn how we can help your brand be found more frequently online and leverage AI traffic insights to boost your strategy.

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