mmm-eval

An evaluation framework for Marketing Mix Models (MMM).

Overview

mmm-eval provides a standardized approach for evaluation and comparison of different MMM frameworks using a full suite of validation tests including holdout accuracy, in-sample accuracy, cross-validated holdout accuracy, refresh stability, perturbation, and placebo metrics.

Features

• Multi-framework support: Evaluate PyMC-Marketing and Google Meridian models
• Standardized metrics: Consistent evaluation across different frameworks
• Easy to use: Simple CLI interface and Python API
• Extensible: Add new frameworks and tests easily

Quick Start

Installation

You can install mmm-eval directly from the repository:

pip install git+https://github.com/mutinex/mmm-eval.git

Requirements

mmm-eval currently supports Python 3.11 and 3.12 only.

If you’re building locally with Poetry, make sure you have Poetry 2.x installed.

Basic Usage

# Run with default settings
mmm-eval --input-data-path data.csv --framework pymc-marketing

# Run with custom configuration
mmm-eval --input-data-path data.csv --framework pymc-marketing --config-path config.json --output-path results/

# Run specific tests
mmm-eval --input-data-path data.csv --framework pymc-marketing --test-names holdout_accuracy in_sample_accuracy cross_validation

Documentation

The official hosted documentation can be found here.

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.