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Further Reading — Papers, Articles, and External Resources

A curated collection of resources for deeper learning about marketing mix modeling, Bayesian statistics, and the methodologies behind Simba.

Marketing Mix Modeling

Foundational Concepts

Industry Reports

Bayesian Statistics

Introductory Resources

  • "Bayesian Data Analysis" by Gelman et al. — The definitive textbook on Bayesian statistics (advanced but comprehensive)
  • "Statistical Rethinking" by Richard McElreath — An accessible introduction to Bayesian modeling with practical examples
  • "Think Bayes" by Allen Downey — A beginner-friendly introduction to Bayesian statistics using Python

PyMC Resources

Media Effectiveness

Saturation and Diminishing Returns

Adstock and Carryover

Privacy and the Future of Measurement

  • The deprecation of third-party cookies, iOS App Tracking Transparency (ATT), GDPR, and similar regulations are making user-level attribution increasingly unreliable. MMM's reliance on aggregate time-series data makes it inherently privacy-compliant.

Open-Source MMM Tools

  • PyMC-Marketing — The open-source Bayesian marketing analytics library (Simba's foundation)
  • Robyn by Meta — Meta's open-source MMM solution (R-based, ridge regression approach)
  • Meridian by Google — Google's open-source Bayesian MMM tool

Conferences and Communities

  • PyMCon — The PyMC community conference featuring talks on Bayesian statistics and applications
  • Marketing Science Conference — INFORMS conference on quantitative marketing research
  • Measure Camp — Unconference for analytics and measurement professionals

Have a resource suggestion? Let us know.

See also: Glossary | PyMC-Marketing & Simba | Core Concepts