This project is about benchmarking various casual inference/ uplift modeling approaches on four datasets to optimize marketing campaigns. The used models are the following:
- Causal Honest Tree
- Causal Honest Forest
- Causal Boosting
- Causal Bayesian Additive Regression Trees
We found that using causal model for targeting in marketing campaigns would yield additional 50.000€.