The AI Search Traffic Tracker

It's no secret that traditional search is dying. Buyers are increasingly skipping Google entirely and moving towards platforms like Perplexity, ChatGPT, and Claude to research solutions, compare vendors, and to find answers.

If your brand gets recommended, these AI engines drop a citation link. When a user clicks that link, they land on your site.

The problem? if your company gets recommended, AI engines don't always drop a citation link; therefore, marketing teams are left in the dark about this traffic, labelling them as generic "Referral" or "Direct" buckets.

How can this hack help?

Instead of guessing what keywords to optimise for a traditional search algorithm, you get a data-backed roadmap showing exactly what complex topics, structures, and formats are winning the Answer Engine Optimisation (AEO) game. This insight gives marketers the option to be

Phase 1: Build the "AI-Referenced Audience" Active List

Step 1: Create a New Active List

Navigate to CRM > Lists.
Click Create list in the top right.
Select Contact-based and choose Active list
Suggested name convention [GEO] AI-Referred Leads (Perplexity/OpenAI).

Step 2: Configure the Source Filters

Click Add filter and select Contact properties.
Search for and select original source drill-down 1.
Set the criteria to contain any of and paste the following common AI domains :
- perplexity.ai
- openai.com
- chatgpt.com
- anthropic.com
- claude.ai
Click Back, then click AND/OR to add an OR branch.
Select Contact properties > Original source drill-down 2.
Set to contains any of and paste the same strings:
- perplexity.ai
- openai.com
- chatgpt.com
- anthropic.com
- claude.ai

Top Tip: AI search setups evolve rapidly. Keep an eye on your standard traffic analytics. If you see new AI tools appearing in your referral traffic, manually add their domains to this active list filter.

Step 3: Save and Populate

Click Save list in the top right. HubSpot will begin processing your historical data to pull in any contacts who originally found you via these engines.

Phase 2: Build the AI-Landing Page Reporting Matrix

Now that you have created your list, you need to see exactly where they landed so your content team knows what the AI engines are recommending.

Step 1: Create a Custom Report

Navigate to Reporting > Reports > Create report.
Select the Custom Report Builder.
Choose Contacts as your primary data source.

Step 2: Filter by Your New List

In the left sidebar of the report builder, go to the Filters tab.
Add the filter: List membership | is member of | [GEO] AI-Referred Leads (Perplexity/OpenAI).
Ensure your date property filter (e.g., Create date) is set to is all time or your desired tracking window.

Step 3: Configure the Visualisation

Change the chart type to a Table or a Horizontal Bar Chart.
Rows / X-Axis: Search for and drag in the contact property First page seen. (This reveals the exact URL they landed on when the AI engine sent them to your site).
Values / Y-Axis: Drag in Count of Contacts.
Sort the table by Count of Contacts in descending order.
Click Save and add it to your Marketing Dashboard.

Phase 3: Actioning the Data (The Content Roadmap)

Once your reporting matrix populates, you will see a clear list of URLs. These pages represent your AI Trust Footprint. Below are some suggestions of how you can optimise these pages.

1. Double-Down on Successful Content Architectures

Analyse the layout of the winning pages.

Do they feature clear <h2> or <h3> question headers?
Do they have bulleted summaries or TL;DR blocks at the top?

2. Implement "Value-Hooking" on These Pages

The users arriving from AI engines already have a high-intent answer from the AI chatbot; they clicked your link to go deeper.

Ensure these specific landing pages have contextual, low-friction call-to-actions (CTAs) like templates, calculators, or deep-dive PDFs rather than aggressive "Book a Demo" pop-ups. Maximise the conversion rate of this highly qualified traffic.

Mel Baker

HubSpot Marketing Consultant