AI native marketing | Online course: Measure the modern AI-powered B2B funnel
Build a measurement framework that tracks dark funnel, AI-driven touch points, and pipeline in one system
Instructors: Jeff Sauer, Julie Brade, Manisha Mistry
Trained 50,000+ marketers across 10,000+ organizations (e.g., Electrolux, Target, Nestlé, 3M) and built a 5x Inc. 5000 agency.
Map AI-driven journeys, identify LLM traffic in GA4, and report accurate pipeline impact with clean, AI-ready data.
- Map the AI-first B2B funnel and modern buyer journeys
- Identify and label AI traffic in GA4 and GTM
- Clean and standardize your measurement foundation
- Query GA4 data directly using AI and MCP
- Report AI impact with clear dashboards and narratives
This live course has come to an end.
We are working on an on-demand version.
Trusted by marketers at
Measure AI demand with a clear system
AI traffic doesn’t behave like traditional search, and GA4 wasn’t built to make it obvious.
Identify and label LLM traffic in GA4, clean up your measurement foundation, and connect activity to pipeline impact.
Build dashboards and narratives that clearly prove what AI is doing for your business.
This course removes the black box from your AI reporting.
Part 01: The AI traffic measurement problem
B2B buyers now compare and shortlist vendors inside AI tools before they ever reach your site. That shift creates a blind spot in analytics and a new measurement foundation for understanding AI-driven demand.
- How B2B discovery moved from search to AI chat
- Zero-click discovery and the compressed buying funnel
- Broken last-click attribution
- Conversion rate data: ChatGPT vs. Google Organic
- The dark funnel: what’s invisible and why it still counts
- What GA4 does and doesn’t show you by default
Part 02: AI identification in GA4 & GTM
AI traffic is already showing up, but it is often hard to see and easy to misclassify. GA4 custom channel groups and GTM-based first-party cookies help reveal AI referrals, organize them properly, and preserve source data that would otherwise disappear into direct traffic.
- Identify AI traffic and isolate it from other sources
- AI traffic reports in GA4
- GTM tagging for AI
- GTM mini audit
Part 03: MCP setup and GA4 queries
Claude connects directly to GA4 through MCP, turning prompts into answers from your analytics data. Live querying, interactive reports, and reusable Skills make repeatable analysis possible without rebuilding dashboards in Looker Studio.
- Setting up an MCP server
- Querying GA4 data through the MCP
- Using skills to automate AI traffic reports
- Other useful MCP servers for marketers
Part 04: AI traffic and visualization in Data Studio
AI traffic measurement becomes useful when it is visible in a reporting view clients can access easily. The GA4 channel group, GTM custom dimensions, and MCP queries come together in a reusable Data Studio dashboard that compares AI traffic against every other channel and gives the data enough context to support decisions.
- GA4 reporting with custom dimensions
- Building custom channel groups and reporting in Data Studio
- The AI traffic dashboard template
Meet your instructors
Jeff Sauer
Founder @ MeasureU
Founder of MeasureU who’s helped 50,000+ marketers turn analytics into better decisions, and built a five-time Inc. 5000 agency.
Director of Measurement at MeasureU who’s trained dozens of teams to measure performance and improve the user journey.
THIS TRAINING IS PART OF THE AI NATIVE MARKETER SUBSCRIPTION:
Become the AI native marketer who ships the work of three.
Every two weeks, CXL helps you build one AI native workflow you can actually use at work. You only prep what matches your level, then build live with a top 1% operator.
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AI makes you faster at tasks you already did. The work itself has not changed.
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You have rebuilt whole workflows around AI and ship work that used to need a specialist.
You can tell because: you no longer wait on a designer, a writer, or an analyst for your core work.
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You build systems other people run and cover scope that used to take two or three people.
You can tell because: your team runs on workflows you designed.
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