1 Malleswar Rao, 2 Ch Madhumathi, 3 K Nagakruthika, 4 Ch Devaji, 5 G Gowtham Raj 03 09 The Ecommerce Cart Abandonment Rate Analysis system is a data analytics and visualization platform designed to monitor and analyze customer behavior during the online shopping process Cart abandonment occurs when customers add products to their shopping cart but leave the website or application without completing the purchase A high abandonment rate can result in lost sales and may indicate problems in pricing checkout experience shipping costs payment methods or customer engagement The proposed system collects ecommerce activity data such as customer sessions product views cart additions cart removals checkout attempts completed orders product categories device types traffic sources and timestamps The system processes this information to calculate important metrics such as cart abandonment rate checkout completion rate conversion rate average cart value and abandoned cart value The dashboard presents the analyzed information using interactive charts graphs tables funnel diagrams and Key Performance Indicators KPIs Business users can observe how customers move from product browsing to cart creation checkout and final purchase Filters allow users to analyze abandonment patterns based on product category device traffic source customer segment and time period The system can identify stages in the shopping journey where customers frequently leave without purchasing It can also highlight changes in abandonment rates over time and compare customer behavior across different categories and devices These insights can help businesses investigate potential checkout issues and improve the overall shopping experience Overall the Ecommerce Cart Abandonment Rate Analysis system provides a centralized platform for understanding shoppingcart behavior and lostconversion patterns It reduces manual analysis and supports datadriven ecommerce optimization Future enhancements can include AIbased abandonment prediction personalized recovery campaigns checkout optimization recommendations customer segmentation realtime alerts and intelligent product or offer recommendations Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026