facebookexperimental / Robyn
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.
β1,287Updated this week
Alternatives and similar repositories for Robyn
Users that are interested in Robyn are comparing it to the libraries listed below
Sorting:
- LightweightMMM π¦ is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channeβ¦β963Updated last month
- Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.β829Updated this week
- Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROASβ377Updated 2 years ago
- GeoLift is an end-to-end geo-experimental methodology based on Synthetic Control Methods used to measure the true incremental effect (Lifβ¦β200Updated 10 months ago
- Python Class created to address problems regarding Digital Marketing Attribution.β327Updated 7 months ago
- Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.β636Updated 4 months ago
- β88Updated last year
- An R package for causal inference in time seriesβ1,739Updated last year
- siMMMulator is an open source R-package that helps users to generate simulated data to plug into Marketing Mix Models (MMMs). The packageβ¦β50Updated last year
- A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inferenceβ¦β104Updated last year
- An open-source implementation of the geo experiment analysis methodology developed at Google. Disclaimer: This is not an official Google β¦β136Updated 5 years ago
- Matched Markets is a Python library for design and analysis of Geo experiments using Matched Markets and Time Based Regression.β88Updated 2 months ago
- A Python package for causal inference in quasi-experimental settingsβ982Updated this week
- (ml) - python implementation of bayesian media mix modelling with shape and carryover effectβ58Updated 3 years ago
- GeoLift is an end-to-end geo-experimental methodology based on Synthetic Control Methods used to measure the true incremental effect (Lifβ¦β10Updated 3 years ago
- Building an ML model to identify ROIs on marketing campaigns and their impacts on sales and customer conversions.β14Updated 3 years ago
- β113Updated last year
- A list of blogs, videos, and other content that provides advice on building experimentation and A/B testing platformsβ157Updated 2 years ago
- LTVision is an open-source library from Meta, designed to empower businesses to unlock the full potential of predicted customer lifetime β¦β81Updated this week
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.β1,966Updated 2 months ago
- Multi-Touch Attributionβ116Updated 3 years ago
- A PoC for a fractional attribution model leveraging first order Markov Chains.β79Updated 7 months ago
- β134Updated last year
- Lifetime value in Pythonβ1,464Updated 10 months ago
- A package to compute a marketing mix model.β70Updated last year
- CausalLift: Python package for causality-based Uplift Modeling in real-world businessβ348Updated 2 years ago
- β191Updated 3 months ago
- This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design forβ¦β69Updated last year
- Code for the Book Causal Inference in Pythonβ312Updated last year
- β53Updated 3 years ago