https://facebookexperimental.github.io/Robyn/
Robyn is an automated Marketing Mix Modeling (MMM) open source code.
Open Source and Automated Marketing Mix Modeling
Robyn is an automated Marketing Mix Modeling (MMM) code. It aims to reduce human bias by means of ridge regression and evolutionary algorithms, enables actionable decision making providing a budget allocator and diminishing returns curves and allows ground-truth calibration to account for causation
Reduces human bias
- Automated hyperparameter optimization with evolutionary algorithms from Facebook's AI library Nevergrad
- Ridge regression with cross-validation to regularize multi-collinearity and prevent overfitting
- Facebook's Prophet library to automatically decompose the trend, seasonality and holidays patterns
Aligns with the ground-truth
- It calibrates models based on ground-truth methodologies (Geo-based, Facebook lift, MTA, etc.)
- Facebook Nevergrad's multi-objective optimization minimizing the error between MMM prediction and ground-truth
Enables actionable decision making
- Budget allocator using a gradient-based constrained non-linear solver to maximize the outcome by reallocating budgets
- Enables frequent modeling outcomes due to stronger automation
- Allows intuitive model comparisons via automatically generated model one-pagers
Private by Design
- Privacy friendly, with no requirement for PII or Individual log level data
- Not dependent on Cookies or Pixel data
Robyn Code Walkthrough Video
Please watch this walkthrough video to understand better how the code works