Data-Driven Solution for Insurance Sales Conversion

This project aimed to increase the conversion rates of up-sell, cross-sell, and down-sell for Santander's insurance products, which were initially at 5%. The solution used a machine learning model (K-means clustering) to target the best clients for each type of sale.

The end-to-end solution involved data acquisition, ETL, data processing, and training the K-means model. It also included the creation of a dashboard that guided the sales team in making targeted calls, based on key variables such as age, income, tenure, and existing products. The project resulted in an improved conversion rate from 5% to 8%, significantly enhancing the sales process.