Robyn
Robyn is an experimental, ML-powered and semi-automatetd Marketing Mix Modeling (MMM) open source package.
A New Generation of Marketing Mix Modeling
Robyn aims to reduce human bias in the modeling process, esp. by automating modelers decisions like adstocking, saturation, trend & seasonality as well as model validation. Moreover, the budget allocator & calibration enable actionability and causality of the results.
Reduces human bias
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