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.

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

Marketing Mix Modeling Data Generator

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

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.

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

Marketing Mixed Modelling using PyMC3-Marketing

PySiMMMulator is an open source Python adaption of the R-package siMMMulator, which allows users to generate simulated data to use in testing Marketing Mix Models (MMMs).

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.

In order to inform decisions about an optimal marketing budget, the project uses multiple regression analysis to assess the impact of TV, radio, and newspaper ad budgets on Company X's sales.

Applied paper using VAR and VEC models on the Nielsen cookies dataset. This was the final assignment for the Advanced Econometrics course at the São Paulo School of Economics, Getulio Vargas Foundation, with a focus on time series analysis.

Built Marketing Mix Model (MMM) using e-commerce data to analyze the impact of various marketing methods.