google / lightweight_mmmLinks
LightweightMMM π¦ is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
β980Updated last month
Alternatives and similar repositories for lightweight_mmm
Users that are interested in lightweight_mmm are comparing it to the libraries listed below
Sorting:
- Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROASβ384Updated 3 years ago
- Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.β911Updated this week
- Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission isβ¦β1,325Updated last month
- GeoLift is an end-to-end geo-experimental methodology based on Synthetic Control Methods used to measure the true incremental effect (Lifβ¦β204Updated last year
- Python Class created to address problems regarding Digital Marketing Attribution.β334Updated 10 months ago
- Matched Markets is a Python library for design and analysis of Geo experiments using Matched Markets and Time Based Regression.β92Updated 4 months ago
- β88Updated 2 years ago
- Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.β643Updated 6 months ago
- A package to compute a marketing mix model.β70Updated 2 years ago
- This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design forβ¦β71Updated 2 years ago
- A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inferenceβ¦β114Updated last year
- LTVision is an open-source library from Meta, designed to empower businesses to unlock the full potential of predicted customer lifetime β¦β92Updated 2 months ago
- β97Updated last month
- Multi-Touch Attributionβ117Updated 3 years ago
- β117Updated last year
- A PoC for a fractional attribution model leveraging first order Markov Chains.β83Updated 10 months ago
- Data-Driven Marketing Attributionβ33Updated 4 years ago
- Transparent, robust and trustworthy A/B experimentation for Shopping feeds.β48Updated 2 months ago
- (ml) - python implementation of bayesian media mix modelling with shape and carryover effectβ58Updated 3 years ago
- A Python package for causal inference in quasi-experimental settingsβ1,026Updated this week
- β54Updated 3 years ago
- A flexible python package for cost-aware uplift modelling.β35Updated 11 months ago
- β26Updated 3 weeks ago
- A list of blogs, videos, and other content that provides advice on building experimentation and A/B testing platformsβ160Updated 2 years ago
- Marketing attribution using Bayesian credible sets and regression methodsβ15Updated 5 years ago
- CausalLift: Python package for causality-based Uplift Modeling in real-world businessβ351Updated 2 years ago
- Open source marketing mix modeling code for vexpower.comβ44Updated 4 years ago
- An open-source implementation of the geo experiment analysis methodology developed at Google. Disclaimer: This is not an official Google β¦β139Updated 5 years ago
- Predict customer lifetime value using AutoML Tables, or ML Engine with a TensorFlow neural network and the Lifetimes Python library.β169Updated last year
- Markov Model for Online Multi-Channel Attributionβ11Updated last year