Design a Geo-Experiment in 30 Minutes with Claude Code

Hosted by Guilherme Diaz-Berrio

Thu, Apr 9, 2026

11:30 AM UTC (45 minutes)

Virtual (Zoom)

Free to join

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Marketing Science Bootcamp: MMM, Attribution and Experiments with Claude Code
Gui Diaz-Berrio
View syllabus

What you'll learn

See Claude Code design a geo-experiment in 30 minutes

From power analysis to market selection — watch agentic AI handle the heavy lifting while you make the decisions.

Catch the design flaws that kill experiments — fast

Wrong MDE, underpowered tests, confounded markets. See how Claude Code flags broken designs before you spend a dollar.

Evaluate results with AI-assisted statistical rigor

Was the lift real or noise? See how Claude Code runs the validation so you deliver a clear answer, not a hedged one.

Why this topic matters

Most marketing experiments fail, not because the idea was wrong, but because the design was. Teams rush past power analysis, pick test markets based on convenience, and set MDE thresholds that guarantee either a false positive or an inconclusive result. Then when results come in, evaluation is either too slow or too uncertain. "we think it worked, but we're not sure" doesn't move budget decision.

You'll learn from

Guilherme Diaz-Berrio

Co-founder @ Pinemarsh and author of "Data Analytics for Marketing"

What you'll see in 30 minutes is one session's worth of material.


The full 4-week cohort (starting May 2026) covers the complete stack:

  • Context window management for long analytical sessions
  • Building custom Claude Code Skills that encode your team's modeling standards
  • End-to-end data pipelines — from raw data to executive-ready deliverables
  • Marketing Mix Modeling and Geo-Experimentation, orchestrated agenically
  • Automating recurring measurement workflows so they run without you


Join the waitlist to get early access and priority enrollment for the May cohort of Marketing Science Bootcamp with Claude Code.


Gui Diaz-Berrio has led marketing measurement at companies spending €100M+ on advertising, including Kindred Group (Head of Marketing Analytics) and enterprise clients through Pinemarsh Consulting. He's built models from scratch and managed vendor relationships — both perspectives taught in this course.

Author of "Data Analytics for Marketing with Python" (Packt, 2024) — covering the practical frameworks taught in this course.

He's faced the challenges you're dealing with — messy data, skeptical CFOs, vendor black boxes, and the pressure to prove ROI with limited experimentation budget.

Previously at

Kindred
BMW Group
@Packtpub
Dampi Bowl 🥥🍍🌶

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