A Deep Learning Framework for E-Commerce Cart Abandonment Prevention: Multi-Factor Analysis and Real-Time Intervention

Author(s)	Anirudh Reddy Pathe
Country	United States
Abstract	It’s a common experience in e-commerce that cart abandonment rates can be above 70% therefore causing huge losses in sales revenues. Herein, this paper propounds a real-time cart abandonment prediction and prevention framework based on deep learning. It combines a behavioral, a transactional, and a contextual model using multi-factor analysis to predict abandonment and deliver appropriate recommendations. For temporal data, recurrent neural networks (RNNs) are used, and for spatial data, convolutional neural networks (CNNs) are used to analyze the information; additionally, reinforcement learning models give real-time recommendations such as discounts for particular consumers or future notifications. The present research proves the effectiveness of deep learning approach of improving customer retention rates and revenue recovery.
Keywords	Shopping Cart Abandonment, Electronic Commerce, Neural Network, Recurrent Neural Network, Markov Decision Process, Customer Behavior Analytics, Real-Time Interaction
Published In	Volume 14, Issue 1, January-June 2023
Published On	2023-04-05
Cite This	A Deep Learning Framework for E-Commerce Cart Abandonment Prevention: Multi-Factor Analysis and Real-Time Intervention - Anirudh Reddy Pathe - IJAIDR Volume 14, Issue 1, January-June 2023. DOI 10.5281/zenodo.14598821
DOI	https://doi.org/10.5281/zenodo.14598821
Short DOI	https://doi.org/g8xpkb

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