A Coupon Usage Prediction Algorithm Based On XGBoost

Coupon personalized placement recommendations are presented in this paper, which use XGBoost algorithm to predict whether coupons are used by users for a certain period of time. In this paper, grid search method was used to adjust the parameters, and the model was continuously optimized. The final AUC value of the model was 0.8496, and suggestions were made for personalized coupons, thereby increasing merchant sales and increasing profits. Experimental results demonstrate that personalized coupons based on the XGBoost algorithm can better contribute to precision marketing.