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A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more

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awesome-marketing-machine-learning

A curated list of awesome machine learning libraries for marketing. Inspired by both awesome-production-machine-learning and awesome-machine-learning, and created and maintained by Station 10.

Note that some packages could fit into more than one section. This has been noted in the descriptions so be sure to Ctrl + F as well as exploring by sections.

Want to contribute? Please raise a Pull Request or an issue. If you find this useful please drop a ⭐️. This helps motivate us and others to update and maintain the list.

All packages are Python based unless otherwise stated. We welcome contributions from R Users!

Main Content

Attribution

Causal Inference

  • CausalImpact Github Stars (R) Causal Inference using Bayesian structural time-series models by Google.
  • causalml Github Stars Uplift modeling and causal inference with ML by Uber.
  • CausalPy Github Stars Causal Inference & Synthetic Control. Supports fitting with scikit-learn and PyMC models.
  • dowhy Github Stars Causal Inference that supports explicit modeling and testing of causal assumptions.
  • SyntheticControlMethods Github Stars Causal inference using Synthetic Control.
  • tfcausalimpact Github Stars Google's CausalImpact Algorithm implemented on top of TensorFlow Probability.
  • upliftml Github Stars Scalable unconstrained and constrained uplift modeling from experimental data using PySpark and H20.
  • scikit-uplift Github Stars
  • Uplift modeling python package that provides fast sklearn-style models implementation, evaluation metrics and visualization tools.

Churn / CLV

Data

  • gapandas4 Github Stars Python package for querying the Google Analytics Data API for GA4 and displaying the results in a Pandas dataframe.

Econometrics

  • EconML Github Stars AI, Econometrics and Causal Inference modelling.
  • statsmodels Github Stars Statistical modeling including time series and econometrics.

Geo Experimentation

  • trimmed_match Github Stars Ad effectiveness through the design and analysis of randomized Geo Experiments by Google.
  • matched_markets Github Stars Time-Based regression matched markets approach for designing Geo Experiments by Google.
  • GeoexperimentsResearch Github Stars (R) Open-source implementation of the geo experiment analysis methodology developed at Google (Archived)
  • GeoLift Github Stars Geo Experimentation methodology based on Synthetic Control Methods used to measure lift of ad campaigns by Facebook.

Media / Marketing Mix Models

  • BayesianMMM Github Stars Bayesian Media Mix mMdelling with shape and carryover effect.
  • dammmdatagen Github Stars (R) Media Mix Modeling Data Generator.
  • lightweight-mmm Github Stars Bayesian Media Mix Models by Google.
  • mamimo Github Stars Small Media Mix Models designed to be used in conjunction with ML libraries (e.g. SKL)
  • mmm-stan Github Stars Multiplicative Media Media Mix Model.
  • pymc-marketing Github Stars Bayesian Media Mix, Adstock, Saturation Customer Lifetime Value & Churn models.
  • Robyn Github Stars (R) Bayesian Media Mix Models by Facebook.

Personalisation / Segmentation

  • amazon-denseclus Github Stars Python module for clustering both categorical and numerical data using UMAP and HDBSCAN by Amazon.
  • rfm Github Stars RFM Analysis and Customer Segmentation.
  • retentioneering-tools Github Stars Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation
  • ecommercetools Github Stars Data science toolkit for those working in technical ecommerce, marketing science, and technical seo and includes a wide range of features to aid analysis and model building.

Recommendation Systems

  • lightfm Github Stars Implementation of LightFM, a hybrid recommendation algorithm.
  • openrec Github Stars Open-source and modular library for neural network-inspired recommendation algorithms.
  • recmetrics Github Stars A library of metrics for evaluating recommender systems
  • recommenders Github Stars Best Practices on Recommendation Systems by Microsoft.
  • Surprise Github Stars Scikit for building and analyzing recommender systems that deal with explicit rating data.

Time Series

  • darts Github Stars Python library for user-friendly forecasting and anomaly detection on time series built using SKL conventions.
  • gluonts Github Stars Probabilistic time series modeling, focusing on deep learning based models, based on PyTorch and MXNet.
  • neural_prophet Github Stars Framework for interpretable time series forecasting built on PyTorch.
  • orbit Github Stars Python package for Bayesian time series forecasting and inference by Uber.
  • pmdarima Github Stars
  • Pmdarima is a statistical library designed to fill the void in Python's time series analysis capabilities.
  • prophet Github Stars Additive time series modelling by Facebook.
  • sktime Github Stars A unified framework for ML with Time Eeries.
  • statsforecast Github Stars Lightning ⚡️ fast forecasting with statistical and econometric models.
  • stumpy Github Stars STUMPY computes something called the matrix profile, which is just an academic way of saying "for every subsequence automatically identify its corresponding nearest-neighbor"
  • temporian Github Stars Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖.
  • tbats Github Stars BATS and TBATS time series forecasting
  • tsfresh Github Stars Time Series Feature extraction based on scalable hypothesis tests.
  • tslearn Github Stars The machine learning toolkit for time series analysis in Python.

Survival Analysis

  • lifelines Github Stars lifelines is a pure Python implementation of the best parts of survival analysis.
  • pysurvival Github Stars An open source python package for Survival Analysis modeling.
  • scikit-survival Github Stars Survival analysis built on top of scikit-learn.

Synthetic Control

  • pysyncon Github Stars Multiple Synthetic Control implementations.
  • scpi Github Stars Provides Python, R and Stata implementations of estimation and inference procedures for synthetic control methods.
  • SparseSC Github Stars Sparse Synthetic Control Models in Python by Microsoft.

Synthetic Data

  • Decoy Github Stars Synthetic Data Generator using DuckDB at its core.
  • SDV Github Stars Python library designed to be your one-stop shop for creating tabular synthetic data.