GitHub topics: marketing-science

Repositories

google/lightweight_mmm

LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.

Language: Python - Size: 12.7 MB - Last synced at: 4 days ago - Pushed at: about 1 month ago - Stars: 962 - Forks: 211

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.

Language: Jupyter Notebook - Size: 392 MB - Last synced at: 11 days ago - Pushed at: 12 days ago - Stars: 1,282 - Forks: 388

mplatzer/BTYDplus

R package for Customer Behavior Analysis

Language: R - Size: 929 KB - Last synced at: 6 days ago - Pushed at: about 1 year ago - Stars: 189 - Forks: 48

google-marketing-solutions/ml_toast

Cluster multilingual search terms captured from different time windows into semantically relevant topics.

Language: Python - Size: 153 KB - Last synced at: about 1 month ago - Pushed at: 9 months ago - Stars: 35 - Forks: 7

RyanAugust/PySiMMMulator

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).

Language: Python - Size: 198 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 5 - Forks: 0

nitinjosephrepo/Marketing-Mix-Modeling-MMM-Using-Robyn

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

Language: R - Size: 267 KB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0