Alternatives and similar repositories for Robyn:

Users that are interested in Robyn are comparing it to the libraries listed below

• google / lightweight_mmm
  LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channe…
  ☆946Updated last month
• pymc-labs / pymc-marketing
  Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.
  ☆796Updated this week
• sibylhe / mmm_stan
  Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS
  ☆374Updated 2 years ago
• facebookincubator / GeoLift
  GeoLift is an end-to-end geo-experimental methodology based on Synthetic Control Methods used to measure the true incremental effect (Lif…
  ☆195Updated 8 months ago
• WillianFuks / tfcausalimpact
  Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
  ☆631Updated 2 months ago
• DP6 / Marketing-Attribution-Models
  Python Class created to address problems regarding Digital Marketing Attribution.
  ☆322Updated 5 months ago
• google / matched_markets
  Matched Markets is a Python library for design and analysis of Geo experiments using Matched Markets and Time Based Regression.
  ☆82Updated this week
• Minyus / causallift
  CausalLift: Python package for causality-based Uplift Modeling in real-world business
  ☆346Updated last year
• station-10 / awesome-marketing-machine-learning
  A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference…
  ☆101Updated 10 months ago
• facebookexperimental / siMMMulator
  siMMMulator is an open source R-package that helps users to generate simulated data to plug into Marketing Mix Models (MMMs). The package…
  ☆48Updated last year
• eeghor / mta
  Multi-Touch Attribution
  ☆113Updated 3 years ago
• pymc-labs / CausalPy
  A Python package for causal inference in quasi-experimental settings
  ☆956Updated this week
• google / trimmed_match
  This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for…
  ☆65Updated last year
• google / GeoexperimentsResearch
  An open-source implementation of the geo experiment analysis methodology developed at Google. Disclaimer: This is not an official Google …
  ☆133Updated 5 years ago
• google / CausalImpact
  An R package for causal inference in time series
  ☆1,731Updated last year
• slavakx / medium_posts
  ☆86Updated last year
• DavisTrey / ExperimentationResources
  A list of blogs, videos, and other content that provides advice on building experimentation and A/B testing platforms
  ☆155Updated last year
• leopoldavezac / BayesianMMM
  (ml) - python implementation of bayesian media mix modelling with shape and carryover effect
  ☆58Updated 3 years ago
• hammer-mt / VEX-MMM
  Open source marketing mix modeling code for vexpower.com
  ☆44Updated 3 years ago
• jerednel / markov-chain-attribution
  A PoC for a fractional attribution model leveraging first order Markov Chains.
  ☆77Updated 5 months ago
• Garve / mamimo
  A package to compute a marketing mix model.
  ☆70Updated last year
• facebookincubator / LTVision
  LTVision is an open-source library from Meta, designed to empower businesses to unlock the full potential of predicted customer lifetime …
  ☆74Updated last month
• camille-004 / attribution-modeling
  Building an ML model to identify ROIs on marketing campaigns and their impacts on sales and customer conversions.
  ☆14Updated 3 years ago
• uber / orbit
  A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
  ☆1,958Updated last week
• hammer-mt / hommmer
  A simple Marketing Mix Modeling library for Python
  ☆27Updated 2 years ago
• matheusfacure / python-causality-handbook
  Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
  ☆2,871Updated 3 months ago
• GoogleCloudPlatform / tensorflow-lifetime-value
  Predict customer lifetime value using AutoML Tables, or ML Engine with a TensorFlow neural network and the Lifetimes Python library.
  ☆168Updated 7 months ago
• maks-sh / scikit-uplift
  uplift modeling in scikit-learn style in python
  ☆756Updated last year
• google / tfp-causalimpact
  ☆99Updated last year
• CamDavidsonPilon / lifetimes
  Lifetime value in Python
  ☆1,461Updated 8 months ago