Marketing Science Bootcamp: MMM, Attribution & Incrementality

Cohort-based Course

Master marketing measurement with Python: Build MMM, attribution & incrementality frameworks to optimize spend and prove marketing ROI

Previously at

BMW Group Niederlassung Wien
Kindred
@Packtpub

Course overview

Move from basic metrics to data-driven marketing decisions with proven models

Ready to move beyond basic attribution models and last-click analytics? This intensive 3-week course teaches you to build and implement three essential marketing measurement frameworks: Media Mix Modeling (MMM), Multi-Touch Attribution, and Incrementality Testing.


You'll learn to:

- Build a complete Media Mix Model using PyMC Marketing / Google Merdian / Meta Robyn to optimize your channel mix

- Design and implement attribution frameworks that accurately track customer journeys  

- Create robust incrementality tests to measure true marketing impact

- Learn how to conduct proper calibration with Geo Experiments and Lift Studies

- Combine all three approaches into a comprehensive measurement strategy


This is not just theory - you'll work with real data and Python implementations. Through hands-on projects and live workshops, you'll develop practical skills you can immediately apply to:


- Make data-driven budget allocation decisions

- Prove marketing ROI to stakeholders

- Understand the true impact of each marketing channel

- Build measurement frameworks that drive business growth


Perfect for Marketing Data Analysts and Data Scientists who want to go beyond basic metrics and build sophisticated measurement systems that drive decisions. By the end of this course, you'll have working models and frameworks you can adapt to your organization's needs.


Course includes:

- 6 live interactive sessions

- Hands-on projects with real data

- Python code templates and implementations

- Direct feedback on your work

- Community of marketing analytics professionals


Prerequisites:

- Basic Python knowledge

- Marketing fundamentals  

- Access to Python environment (instructions provided)

Who is this course for

01

Analytics Managers who need to optimize channel spend and prove ROI to stakeholders, ready to implement data-driven measurement systems

02

Data Analysts struggling with accurate channel attribution who want to build robust testing frameworks and optimize marketing spend

03

Data Scientists who want to move beyond basic attribution and need technical skills to build and implement advanced measurement models

What you’ll get out of this course

Build and deploy a media mix model using real campaign data to optimize your marketing budget allocation across channels.

Build and deploy a complete media mix model using PyMC Marketing / Google Meridian / Meta Robyn. Handle real campaign data, implement adstock and saturation effects, and create actionable budget recommendations with confidence intervals.

Design and implement an attribution framework that accurately tracks customer journeys and validates channel performance

Build a complete attribution system that tracks full customer journeys. Compare first-touch to algorithmic models, validate channel performance, and create actionable reports for stakeholders.

Create and execute incrementality tests to measure the true causal impact of marketing activities on business metrics

Design statistically valid incrementality tests with proper power analysis and sample size calculations. Learn to control for multiple testing, validate results, and measure true lift across marketing channels.

Develop a comprehensive measurement strategy that combines MMM, attribution, and incrementality insights for stakeholder buy-in.

Develop a comprehensive measurement strategy that combines MMM, attribution, and incrementality insights for stakeholder buy-in.

What’s included

Guilherme Diaz-Berrio

Live sessions

Learn directly from Guilherme Diaz-Berrio in a real-time, interactive format.

Lifetime access

Go back to course content and recordings whenever you need to.

Community of peers

Stay accountable and share insights with like-minded professionals.

Certificate of completion

Share your new skills with your employer or on LinkedIn.

Maven Guarantee

This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.

Course syllabus

6 live sessions • 16 lessons • 6 projects

Week 1

Jun 16—Jun 22

    Jun

    17

    MMM Foundations Workshop

    Tue 6/174:00 PM—6:30 PM (UTC)

    Jun

    19

    MMM Implementation

    Thu 6/194:00 PM—6:30 PM (UTC)

    Module 1: MMM Foundations

    3 items

    Module 2: Building Your MMM

    4 items

Week 2

Jun 23—Jun 29

    Jun

    24

    Attribution Framework Design

    Tue 6/244:00 PM—6:30 PM (UTC)

    Jun

    26

    Advanced Attribution

    Thu 6/264:00 PM—6:30 PM (UTC)

    Module 3: Attribution Fundamentals

    3 items

    Module 4: Advanced Attribution

    3 items

Week 3

Jun 30—Jul 6

    Jul

    1

    Experimentation Workshop

    Tue 7/14:00 PM—6:30 PM (UTC)

    Jul

    3

    Integration & Presentation

    Thu 7/34:00 PM—6:30 PM (UTC)

    Module 5: Experimentation Design

    6 items

    Module 6: Integrated Measurement

    3 items

Meet your instructor

Guilherme Diaz-Berrio

Guilherme Diaz-Berrio

Marketing analytics author & leader with 10+ years building measurement systems

As a marketing analytics leader, I've built and scaled measurement frameworks that process millions of customer touchpoints for global organizations.


My experience includes implementing attribution systems, developing media mix models, and creating incrementality testing frameworks that prove true marketing ROI, from BMW Group to Kindred Group.


This practical experience shaped my book "Data Analytics for Marketing with Python" (Packt, 2024), where I share proven approaches to measurement that drive decisions.

I've faced the challenges you're dealing with – from messy data to skeptical stakeholders.


As co-founder at Pinemarsh Consulting, I help companies implement the same frameworks we'll cover in this course. My experience spans multiple industries, combining technical Python expertise with strong business acumen.

You won't just learn theory – you'll build working models using real data and learn how to communicate results effectively to stakeholders.

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Marketing Science Bootcamp: MMM, Attribution & Incrementality

Course schedule

4-6 hours per week

  • Tuesdays & Thursdays

    5:00pm - 7:00pm GMT

    Live sessions every Tuesday and Thursday for 3 weeks. Each 90-minute session combines theory and hands-on practice. Tuesday sessions introduce concepts, Thursday sessions focus on implementation. All sessions include breakout rooms and Q&A.

  • Weekly projects

    2 hours per week

    Weekly projects with clear deadlines and templates provided. Office hours available for 1 hour before each live session for implementation support. Continuous feedback via Slack channel. Expect 2-3 hours weekly for project work.

Learning is better with cohorts

Learning is better with cohorts

Active hands-on learning

This course builds on live workshops and hands-on projects

Interactive and project-based

You’ll be interacting with other learners through breakout rooms and project teams

Learn with a cohort of peers

Join a community of like-minded people who want to learn and grow alongside you

Frequently Asked Questions

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Marketing Science Bootcamp: MMM, Attribution & Incrementality