MMM Calibration: Engineering Business Impact through Bayesian Lift Integration
Details
🎙️ Speakers: Dr. Juan Orduz, Benjamin Vincent, PhD,
Carlos Eduardo Trujillo Agostini, and Will Dean | ⏰ Time: 15:00 UTC / 8:00 AM PT / 11:00 AM ET / 5:00 PM Berlin
Your MMM drives multi-million dollar budget allocations, but can you prove its ROAS estimates are real? Uncalibrated models risk massive waste by ignoring the "ground truth" of experiments.
As leaders in Bayesian media measurement, PyMC Labs is at the forefront of engineering certainty into marketing analytics. Join Juan Orduz and our panel of experts for a deep dive into the technical framework and business impact of MMM calibration. We will move beyond theory to show you how to anchor your models in experimental truth, ensuring your media mix is a strategic growth engine rather than a "black box."
### What You Will Learn
By attending this webinar, you will gain a comprehensive understanding of how to bridge the gap between advanced Bayesian modeling and measurable ROI:
- Constraining ROAS with Prior Predictive Modeling: Learn how to use priors to keep your return on investment estimates within realistic, data-backed boundaries.
- The Power of ROAS Parameterization: Explore the practical applications of Google’s research on parameterization to improve model stability and accuracy.
- Calibration via Additional Likelihoods: Discover how to integrate external lift test data directly into your MMM to validate and refine your results.
- Advanced Geo-Level Calibration: A deep dive into using CausalPy for high-precision experiments at the geographic level.
- Overcoming Organizational Challenges: Understand the operational and strategic hurdles of implementing a calibrated measurement framework within your team.
📜 Outline of Talk / Agenda:
- 5 min: Introduction to PyMC Labs and speakers
- 40 min: Panel discussion
- 15 min: Q&A
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💼 About the speakers:
Dr. Juan Orduz ( Principal Data Scientist at PyMC Labs)
Mathematician (Ph.D., Humboldt Universität zu Berlin) and data scientist with more than 8+ years of industry experience in the Tech sector. He is interested in interdisciplinary applications of mathematical methods, particularly time series analysis, Bayesian methods, and causal inference.
Connect with Dr. Juan: 👉 Linkedin 🧩 Github
Dr. Benjamin Vincent ( Principal Data Scientist at PyMC Labs)
Senior Data Scientist and Lead at PyMC Labs, where he specializes in Bayesian data analysis, causal inference, and decision science. With a background that bridges the gap between rigorous academic research and practical business solutions, Ben is a key contributor to the PyMC ecosystem.
Connect with Benjamin: 👉 LinkedIn🧩 Github
Carlos Eduardo Trujillo Agostini **(**Principal Data Scientist at PyMC Labs)
Carlos is a Marketing Scientist passionate about using data and AI to turn marketing strategy into measurable results. He’s worked with teams across Latin America, Europe, and Africa, including roles at Wise, Bolt, and Omnicom Media Group. As a core member of PyMC Labs, he contributes to open-source projects like PyMC-Marketing, blending statistical rigor with practical marketing insight.
Connect with Carlos: 👉 Linkedin 🧩 Github
Will Dean **(**Principal Data Scientist at PyMC Labs)
Statistician and Data Scientist specializing in geospatial and user analytics. With a deep interest in Bayesian methods, he focuses on transforming complex data into clear, meaningful insights through visualization. His work bridges analytics and software design, exploring how thoughtful engineering can make solving data challenges both simpler and more engaging.
Connect with Will 👉 Linkedin 🧩 Github
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📖 Code of Conduct:
Please note that participants are expected to abide by PyMC's Code of Conduct.
Connecting with PyMC Labs:
🌐 Website: https://www.pymc-labs.com/
👥 LinkedIn: https://www.linkedin.com/company/pymc-labs/
🐦 Twitter: https://twitter.com/pymc_labs
🎥 YouTube: https://www.youtube.com/c/PyMCLabs
🤝 Meetup: https://www.meetup.com/pymc-labs-online-meetup/
🎮 Discord: https://discord.gg/9kuuqhBR