[Online] Bayesian Methods in Modern Marketing Analytics - 31th May, 2023


Date and Time:


To join the event:

Event Description:

During the webinar, we will discuss some of the most crucial topics in marketing analytics: media spend optimization through media mix models and experimentation, and customer lifetime value estimation. We will approach these topics from a Bayesian perspective, as it gives us great tools to have better models and more actionable insights. We will take this opportunity to describe our join with PyMC Labs in open-sourcing some of these tools in our brand-new pymc-marketing Python package.

Outline of Talk / Agenda:

  • 5 min: Intro to PyMC Labs and speakers
  • 45 min: Presentation, panel discussion
  • 10 min: Q&A

About the speaker:

  1. Dr. Juan Camilo Orduz
    Mathematician (Ph.D. Humboldt Universität zu Berlin) and data scientist. Interested in interdisciplinary applications of mathematical methods. In particular, time series analysis, Bayesian methods, and causal inference. Currently, working in marketing data science projects such as media mix modeling, customer lifetime value estimation and experimentation.

    Connect with Juan Orduz:
    LinkedIn: https://www.linkedin.com/in/juanitorduz/
    Twitter: https://twitter.com/juanitorduz
    GitHub: juanitorduz (Juan Orduz) · GitHub
    Website: https://juanitorduz.github.io/

  2. Thomas Wiecki (PyMC Labs)
    Dr. Thomas Wiecki is an author of PyMC, the leading platform for statistical data science. To help businesses solve some of their trickiest data science problems, he assembled a world-class team of Bayesian modelers and founded PyMC Labs – the Bayesian consultancy. He did his PhD at Brown University studying cognitive neuroscience.

    Connect with Thomas Wiecki:
    LinkedIn: https://www.linkedin.com/in/twiecki/
    GitHub: twiecki (Thomas Wiecki) · GitHub
    Twitter: https://twitter.com/twiecki
    Website: https://twiecki.io/

Here are the recording and slides of the webinar