PyMC-Marketing
A Bayesian marketing analytics toolbox for Media Mix Modeling (MMM), Customer Lifetime Value (CLV), and customer choice analysis.
What is PyMC-Marketing?
PyMC-Marketing is a Python library for Bayesian marketing analytics, providing tools to measure marketing effectiveness, predict customer lifetime value, and analyze market choices. It solves the problem of making data-driven marketing decisions under uncertainty by offering probabilistic models that quantify ROI, channel contributions, and customer behavior.
Marketing data scientists, analysts, and researchers who need to build robust, interpretable models for marketing optimization, customer analytics, and product launch impact assessment.
Developers choose PyMC-Marketing because it integrates cutting-edge Bayesian methods with marketing-specific models in an open-source package, offering flexibility, transparency, and uncertainty quantification not always available in proprietary solutions.
Overview
Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.
Use Cases
Best For
- Measuring the ROI of marketing channels with carryover and saturation effects
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