With the rise of AI-powered search engines, many companies have noticed a drop in traditional organic traffic and are now looking to understand which new sources may be filling the gap. Platforms like ChatGPT, Perplexity, Microsoft Copilot, and Gemini are becoming major traffic drivers, and tracking them is key to understanding how users are discovering your content.
In Databox, you can use Google Analytics 4 and Metric Builder to report on sessions coming from AI-based search engines.
How to access the AI Databoard Template
You can add this Databoard Template to your Databox account here: AI (Gen Search) Traffic Overview.
How to measure AI traffic by AI source
Open Metric Builder and select Google Analytics 4 as the Data Source.
Set the Metric to Sessions.
Set the Dimension to Session source.
Add a Filter:
Filter type: Dimension
Dimension: Session source
Operator: Contains a match for the regular expression
Value (copy/paste): .*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.*
Name the Custom Metric (e.g., AI Search Engine Sessions) and save it.
How to measure AI traffic by landing page
To see which pages users from AI tools are landing on:
Open Metric Builder and select Google Analytics 4.
Set the Metric to Sessions.
Set the Dimension to Landing page + query string.
Apply the same Session source filter using the regular expression above.
Save the Custom Metric.
You can now duplicate this Custom Metric and swap in other Metrics (like Users, Engagement Rate, or Conversions), then visualize the data in a table, where each column represents a different Metric and rows represent landing pages.
This approach gives you detailed insight into how AI search engines are driving traffic to your site and what content is performing best.
For more on building Custom Metrics from GA4, visit: How to create Custom Metrics using GA4.