This repository contains the code along with the data for uplift modelling on marketing campaign dataset.
Uplift modeling, also known as incremental modeling is a predictive modeling technique that directly models the incremental impact of a treatment (such as a direct marketing action) on an individual’s behavior.
We trained a Machine Learning model on the Starbucks dataset based on historical data of the customers and their buying patterns and achieved an IRR (Incremental Response Rate) of 2.36% which is 0.88% more than their baseline model. The imbalance in the dataset was handled using SMOTE.