Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.

Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.

Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS

This contains projects based on Algorithmic Marketing like Marketing Mix Modeling, Attribution Modeling & Budget Optimization, RFM Analysis, Customer Segmentation, Recommendation Systems, and Social Media Analytics

This repository contains the code and explanation for market mix modelling technique in economics

Customer & Purchase Analytics using Segmentation, Targeting, Positioning, Marketing Mix, Price Elasticity

A curated list of awesome marketing science resources including geo incrementality testing, media mix models, multi-touch attribution, causal inference, and more from shakostats.com . Star ⭐ the repo if it helps you, and feel free to contribute your own favorite resources

Marketing Mix Modeling Data Generator

This repo contains the project details of the Applied Data Science Course, which is Marketing Mix Models regarding the advertising response measurement.

Karpiu is a package designed for marketing mix modeling by calling Orbit from the backend. Karpiu is still in its beta version. Please use it at your own risk.

Modeling adstock in media mix modeling using Weibull transformations.

A Marketing Mix Modelling project for an E-Commerce company

In this paper we researched the accuracy and usability of machine learning models for MMM analyses.

Marketing Mixed Modelling using PyMC3-Marketing

PySiMMMulator is an open source Python marketing simulation package, which allows users to generate simulated data to use in testing Marketing Mix Models (MMMs).

A New GeneratUsing Robyn aims to reduce human bias in the modeling process, esp. by automating modelers decisions like adstocking, saturation, trend & seasonality as well as model validation. Moreover, the budget allocator & calibration enable actionability and causality of the results

The project analyses the impact of different marketing tactics on the sales of items. The problem is a multivariate-modeling problem as there are 3 different tactics of marketing. Since, the impact of marketing medium cannot be negative we will be using Bayesian model for regression.

Simba — Bayesian Marketing Mix Modeling (MMM) platform. Media attribution, budget optimization, incrementality measurement, and scenario planning. Built on PyMC-Marketing. No-code, fully transparent, enterprise-ready.

An interactive Shiny app for multi-touch attribution (Markov) and a lightweight MMM-style ROI scenario simulator (MMM-lite)—with Diagnostics and Data Health checks to make results easier to trust and explain.

Comprehensive marketing analytics and measurement strategies covering modern data analysis, attribution modeling, and ROI optimization methodologies. Turn data into actionable marketing insights.