Just-Eat.co.uk

FDJ UNITED

BMW Group

@Packtpub

Gui Diaz-Berrio

Cohort - May

Cohort - Oct 20 - Nov 9 

Cohort - Oct 27 - Nov 16

Cohort - Sep 22 - Oct 12 

Cohort - March

Cohort 1

Go from understanding marketing measurement to running it at work — with AI-powered tools you keep forever.

Marketing Analytics Leader & Author

Led measurement for €100M+ in ad spend at Kindred Group & Just Eat Takeaway

Agentic Marketing Science: MMM, Attribution and Experiments with Claude Code

APAC Media Analytics Manager

Data Analyst

data analyst

Head of Performance Marketing

Marketing Manager

Just Eat Takeaway.com

Kindred

Marketing measurement is changing fast. Google Meridian just launched. Bayesian MMM is replacing legacy approaches. Your team is asking for attribution answers you can't deliver with last-click.But the gap between knowing MMM theory and running it is brutal. 54-column datasets where 12 variables will break your model. Thousands of adstock parameter combinations. Meridian errors the docs don't cover. Model outputs you're not sure you can trust.This course closes that gap — with AI doing the heavy lifting.You'll build MMM models (OLS, Bayesian, and Google Meridian), run Shapley and Markov attribution, and design geo-experiments with power analysis. Not toy examples — real pipelines on real data.The difference: you leave with Claude Code Skills — AI-powered tools that automate variable classification, data formatting, and model diagnostics. Run them on your own data, at your job, after the course ends.You don't need to be a Python expert. The Skills handle implementation. You focus on the science and the judgment calls.Early bird: use code EARLYBIRD-MAY26 for 30% off ($450 savings).

You understand marketing science. The code is where it falls apart.

Build Marketing Mix Models from scratch — OLS and Bayesian

Run Google Meridian end-to-end on real multi-geo data

Measure attribution with Shapley values and Markov chains

Design geo-experiments that actually prove incrementality

Leave with Claude Code Skills that work on your own data

You can write a for loop, define a function, and load a CSV with pandas. You do NOT need to be a Python expert — AI handles the heavy code

Working knowledge of Python

You've worked with campaign data, channel spend, or marketing KPIs. You know what impressions, CPM, and ROAS mean in context

Familiarity with marketing or media data

Marketing analyst or data scientist who's been tasked with building in-house measurement but struggles to go from theory to working code

Marketing lead who relies on MMM vendor's black box and wants to understand, validate, and eventually complement or replace their outputs

Data professional who tried Meridian, Robyn, or PyMC-Marketing and hit walls with data formatting, prior specification or debugging errors

Context Engineering for Long Analytics Sessions

Context rot is real: model specs get confused, earlier decisions are forgotten. Learn what causes it and how to spot it

Understand why long sessions break Claude Code

CLAUDE.md design, Skills, session structure. See the patterns that keep Claude Code consistent across a 2-hour analysis

Learn context engineering techniques that work

Walk away with a framework for structuring any long session, so Claude Code stays useful instead of becoming unreliable

Apply this to your own analytical workflows

Design a Geo-Experiment in 30 Minutes with Claude Code

Guilherme Diaz-Berrio

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

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

See Claude Code design a geo-experiment in 30 minutes

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

Catch the design flaws that kill experiments — fast

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

Evaluate results with AI-assisted statistical rigor

Bayesian vs. Frequentist MMM: What Actually Changes

Joint parameter estimation, full posteriors, and priors — explained without the jargon, with side-by-side comparisons.

Understand what Bayesian MMM does differently

Small data, prior knowledge, uncertainty for decisions. Learn the conditions where Bayesian wins and where OLS is fine

Know when Bayesian is worth the complexity

The real advantage: encoding geo-test results as priors. See how Bayesian MMM fuses causal and observational evidence.

See how experiments calibrate Bayesian models

Build a Marketing Mix Model in 30 Minutes with Claude Code

From raw data to budget optimization — watch every step and understand what Claude Code does and why at each stage.

Watch a full Marketing Mix Model get built live in 30 mins

Learn the three guardrails that keep agentic marketing science rigorous, and leave with a diagnostic checklist.

Spot the failure modes of AI-assisted modeling

Get a decision framework for what to automate first — so you leave with a concrete plan, not just inspiration.

Map your workflow to an agentic equivalent

The Deadly Sins of Experimentation

Marketing analytics author & consultant

Marketing Analytics Author & Leader, built measurement systems at global firms

Learn to size and structure experiments with enough power to detect meaningful effects.

How to plan a properly powered experiment

Avoid costly misreads by designing tests that prevent wasted spend and missed growth.

Avoid wasted money & missed opportunities

Build experiments that deliver statistically sound insights you can confidently act on.

Learn directly from Gui Diaz-Berrio

Gui Diaz-Berrio

About Gui

Courses

Agentic Marketing Science: MMM, Attribution and Experiments with Claude Code

Lightning Lessons

Context Engineering for Long Analytics Sessions

Design a Geo-Experiment in 30 Minutes with Claude Code

Bayesian vs. Frequentist MMM: What Actually Changes

Build a Marketing Mix Model in 30 Minutes with Claude Code

The Deadly Sins of Experimentation

The Deadly Sins of Experimentation