In today’s highly competitive market, understanding customer purchasing behavior is key to driving sales performance and optimizing marketing strategies. This competition challenges participants to predict customer purchase intent based on demographic data. By accurately forecasting which customers are most likely to make a purchase, businesses can better target their resources and improve conversion rates.

Participants will work with a real-world anonymized dataset that includes customer segmentation, product attributes, and more. The objective is to develop a machine learning model that can classify whether a customer is likely to purchase or not during a given session or campaign period.

Your model will be evaluated on how accurately it predicts purchase intent on unseen data. Top-performing solutions will have the opportunity to influence real-world decision-making in a production setting.

We encourage creative feature engineering, use of ensemble models, and clear documentation to explain your approach.

Let’s make prediction smarter—together.