Within the banking industry, optimizing telemarketing strategy is a key issue. The problem addressed in our project is the prediction of the success of telemarketing calls for selling long-term deposits by a Portuguese retail bank. We aim to develop machine learning models to assist bank marketing campaign managers in selecting the most promising customers to contact during their campaigns. By analyzing a dataset spanning from 2008 to 2010, we will focus on feature engineering and the comparison of three machine learning models (one stacking system + two strong learners) to determine the most effective approach for predicting campaign success. The goal is to reduce campaign costs, improve customer targeting, and enhance overall marketing campaign efficiency.

Data Source: https://archive.ics.uci.edu/dataset/222/bank+marketing