DYNAMIC DEALS: AI-DRIVEN REAL-TIME COUPON PERSONALIZATION FOR ENHANCED MALL PROFITABILITY

Abstract

In the modern retail environment, customer engagement and retention are key factors driving profitability. Traditional discount strategies and static coupon distributions often fail to match real-time customer preferences, leading to low redemption rates and wasted marketing potential. This study presents “Dynamic Deals”, an AI-driven real-time coupon personalization system designed to enhance shopping mall profitability through intelligent offer targeting. The proposed model integrates customer behavior analytics, location tracking, and machine learning algorithms to deliver customized digital coupons at the optimal time and channel. By leveraging predictive analytics and dynamic segmentation, the system ensures that offers align with customer interests, purchase history, and in-mall behavior. The integration of Explainable Artificial Intelligence (XAI) components enables transparency and interpretability in the coupon recommendation process. Experimental evaluation indicates that Dynamic Deals significantly increases coupon redemption rates and improves revenue conversion compared to traditional methods. This approach demonstrates how AI-powered personalization can transform conventional mall marketing into a data-driven, adaptive ecosystem