talk-data.com talk-data.com

Topic

MMM

Marketing Mix Modeling (MMM)

marketing analytics attribution modeling

1

tagged

Activity Trend

3 peak/qtr
2020-Q1 2026-Q1

Activities

Showing filtered results

Filtering by: PyData Boston 2025 ×
MMM Open- Source Showdown: A Practitioner's Benchmark of PyMC-Marketing vs. Google Meridian

Your Marketing Mix Model is only as good as the library you build it on. But how do you choose between PyMC-Marketing and Google Meridian when the feature lists look so similar? You need hard evidence, not marketing claims. Which library is actually faster on multi-geo data? Do their different statistical approaches (splines vs. Fourier series) lead to different budget decisions?

This talk delivers that evidence. We present a rigorous, open-source benchmark that stress-tests both libraries on the metrics that matter in production. Using a synthetic dataset that replicates real-world ad spend patterns, we measure:

  • Speed: Effective sample size per second (ESS/s) across different data scales.
  • Accuracy: How well each model recovers both sales figures and true channel contributions.
  • Reliability: A deep dive into convergence diagnostics and residual analysis.
  • Resources: The real memory cost of fitting these models.

You'll walk away from this session with a clear, data-driven verdict, ready to choose the right tool and defend that choice to your team.