By late 2024, Google’s global search engine market share fell below 90% for three consecutive months, while AI chatbots rapidly gained momentum in the market. These changes increasingly shape user behavior and expectations. As a result, businesses need to analyze how AI-driven traffic influences their website’s performance.
With Looker Studio, you can identify and segment traffic coming from diverse sources. Besides, to get actionable insights, building intuitive dashboards is easy.
In this guide, we’ll show you how to set up a Looker Studio dashboard to monitor and track AI-referred traffic, including both UTM-tagged and non-tagged referral data. By leveraging SQL queries, you’ll be able to extract vital insights on sources, engagement metrics, and which pages attract traffic from these AI platforms.
Why focus on AI chatbot traffic now?
AI has become an undeniable part of our lives, making things easier both personally and professionally. While it’s hard to predict exactly where it’s headed, sure, it’ll become even more impactful. That’s why businesses are using AI’s power in everything from customer service and lead generation to automating workflows.
This shift is also influencing potential customer behavior. Instead of getting lost in a sea of links offered by search engines, many now prefer instant and quick answers provided by AI searches.
As a result, businesses are focusing on AI-driven traffic to shape their strategies accordingly. However, using traditional methods can sometimes be confusing. For example, without proper tagging and event tracking in Google Analytics 4 (GA4), it’s challenging to tell apart real customer interactions from bot traffic. This lack of segmentation can lead to misleading metrics and uninformed decisions.
Here’s why you should track AI traffic:
- Identify pages receiving AI-driven referrals: Tracking which pages AI tools drive traffic to helps you optimize your content for new search habits.
- Understand which AI tools drive users: Identifying which ones are driving traffic to your website (ChatGPT, Gemini, or others) helps optimize your content strategy, improve user experience, measure AI-driven referrals impact, or else.
- Detect changes in organic traffic sources: AI chatbots are transforming traditional search behaviors. So, monitoring AI chatbot traffic helps you identify any disruption or changes in organic traffic.
Normally, at PEMAVOR, we collect data coming from Consentless Tracking in BigQuery, where we extract the source and medium parameters. Using regex structures within the query, we get insights from the source and medium. Then, we save the results of the query in a table and send it to Looker Studio to visualize it.
However, it’s also possible to gather this data through GA4. Let’s start by explaining that as well.
How to analyze AI traffic using GA4 Exploration Reports
By using a regex formula, you can easily analyze traffic source data in GA4. Explorations allow you to save custom reports for ongoing use.
- Click the Explore icon on the left menu and start a new exploration by selecting Blank.
- Name your exploration (e.g., “AI Traffic”) and set a long date range (e.g., “Last 12 months”).
- Click Create a new segment, select Session segment, and name it (e.g., “AI Traffic”).
- Add a new condition by selecting Page Referrer as the dimension.
- Click Add Filter and set the condition to Matches regex.
Paste the following regex formula:
^https:\/\/(www\.meta\.ai|www\.perplexity\.ai|chat\.openai\.com|claude\.ai|chat\.mistral\.ai|gemini\.google\.com|chatgpt\.com|copilot\.microsoft\.com|copy\.ai)(\/.*)?$|.*\.ai.*|.*\.openai.*|.*\.groq.*|.*\.metaai.*|.*\.meta\.com/ai.*
- Click Apply and save the segment.
- Add dimensions (e.g., Page Referrer and Landing Page + Query String) and metrics (e.g., Sessions, Engagement Rate, and Sessions with Key Events).
- Drag and drop the segment, dimensions, and metrics into their respective fields.
Optional: Change the cell style to Heatmap for a visual overview of the data.
Now, review the report. Which AI platforms drive the most traffic? Which pages attract users from specific AI platforms? Use these insights to optimize your site for AI-driven traffic.
How we set up tracking in Looker Studio
Modern analytics platforms, like Looker Studio, offer advanced capabilities to address these challenges, including customizable dashboards, multi-source integrations, and AI-driven insights. Here’s a step-by-step guide to track AI chatbot traffic using Looker Studio:
1. Create a custom SQL Query
To track AI traffic in Looker Studio, start by creating a Custom SQL Query. This query will pull data from your session and event logs (from Consentless_Data) and use regex to capture AI traffic sources such as ChatGPT, Perplexity, Copilot, Felo and other known platforms.
For those who have limited developer skills can use our free Regex Creator tool as shown below.
2. Define the “AI traffic source”
This term will match the page_referrer or domain with well-known AI chatbot domains using regex. This is essential for identifying the specific AI platform that referred the traffic to your website.
For example, the regex might match:
- chat.openai.com for ChatGPT
- perplexity.ai for Perplexity
- gemini.google.com for Gemini
- copilot.microsoft.com for Copilot
By defining this column, you’ll be able to track and categorize traffic from AI platforms effectively.
3. Track engagement metrics
To gain deeper insights into how users interact with your content, make sure to capture the following engagement metrics:
- Total Users: See how many unique users come to your site via AI platforms.
- Event Counts: Track the number of events users have on your site.
These metrics will help you understand how chatbot-generated answers are influencing user behavior and which parts of your site are most engaging to AI-referred users.
You can track engagement metrics as shown below:
Want to stay ahead of your competitors? Let’s embrace the world of AI and LLMs, and reading about developments on news sites won’t be enough.
Research by Botify indicates that 56% of users preferred AI-generated search results over traditional search engine results pages (SERPs) in certain contexts. In other words, you’ll also need to track AI-referred traffic to properly optimize your visibility and engagement strategies. While dedicated tools for this may emerge in the future, for now, you can monitor this traffic using the steps mentioned above.
Contact us to learn how PEMAVOR’s sophisticated solutions and PPC automation can elevate your Google Ads performance.
