Semi-Automated Marketing Mix Modeling (MMM) from Meta Marketing Science
Adstocking Transformation (Geometric and Weibull)
Check hyperparameter limits
Get correct hyperparameter names
Conduct prophet decomposition
Budget Allocator
Robyn Calibration Function - BETA
Clustering to Reduce Number of Models based on ROI and Errors
Check Models Convergence
Input Data Check & Transformation
Core MMM Function
Evaluate Models and Output Results into Local Files
Build Refresh Model
Response and Saturation Curves
Robyn Modelling Function
Export Robyn Model to Local File [DEPRECATED]
Train Robyn Models
Update Robyn Version
Import and Export Robyn JSON files
Robyn MMM Project from Meta Marketing Science
Hill Saturation Transformation
Set default hyperparameters
Detect and set date variable interval
Michaelis-Menten Transformation
Semi-Automated Marketing Mix Modeling (MMM) aiming to reduce human bias by means of ridge regression and evolutionary algorithms, enables actionable decision making providing a budget allocation and diminishing returns curves and allows ground-truth calibration to account for causation.
Useful links