Reduce the Amount of Push Notifications for E-commerce Apps

                    Reduce the Amount of Push Notifications for E-commerce Apps

Arjarapu Shabarriesh, M B V Sandeep Reddy, A V Rohith Kumar, DR. Sampath A K

Information Science & Technology & Presidency University, Bengaluru

Information Science & Technology & Presidency University, Bengaluru

Information Science & Technology & Presidency University, Bengaluru

Professor in School of Computer Science and Engineering & Presidency University, Bengaluru

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Abstract—Push notifications play a critical role in the engagement strategies of e-commerce apps, but excessive or irrelevant notifications often lead to user frustration, app uninstalls, or opt-outs. Traditional notification strategies, which rely on time-based schedules or trigger-based systems, fail to account for the nuances of user behavior and intent. This project proposes an AI-driven solution to optimize the push notification system by minimizing the number of notifications sent while maximizing their relevance and timeliness. The approach leverages user behavior analysis, predictive modeling, and intent recognition through machine learning algorithms. By monitoring and analyzing user interactions, purchase patterns, and engagement metrics, the AI system identifies moments of genuine purchase intent. Notifications are then strategically sent only when they are most likely to align with the user's current needs and interests.

KEY WORDS: Push notifications, e-commerce apps, notification fatigue, AI-driven solution, user behavior analysis, predictive modeling, machine learning algorithms, personalized notifications, engagement metrics, purchase intent prediction, notification management, real-time data analysis, intent recognition, behavioral analytics, notification optimization.