Enhancing Customer Purchasing Behaviour Prediction in E- Commerce: A Deep Learning Perspective

Rekulara Sharath, Anishetty Vineeth Kumar, Bokkena Sangameshwar, Bidyutlata Sahoo

2025

Abstract

Digital retailers are experiencing a growing volume of online transactions with consumers, which is driven by consumers' ability to buy products through E commerce platforms. Such interactions tend to form complex behavioural constructs that are extractable to assist companies in comprehending consumer requirements. One of the most important applications is the correct determination of the behavior of consumers in the e commerce domain. For selling any sort of product over the Internet or in the other words in order to achieve high profit in an e-commerce business, the interplay between a customer and a merchandise is quite very critical. Moreover, a lot of e commerce websites and services proliferate and competition has become just a mouse-click away. Therefore the need to stay in the business, and enhance profitability measures purchases in a more advanced way predicting desirability and allowing companies to customize services for customers based on their indees. To help forecast behavioral patterns the research will incorporate foam Developing Learning approaches. Also, narrative data from the dataset would be drawn through exploratory data analysis (EDA). The dataset used in this research encompasses of different attributes, such as kind of visitors, that is whether they made a purchase or not and many other variables. In this research, Deep Learning techniques aptly suited for Multi-Level Data due to its robust capacity of modeling and accurate categorization are employed. In addition to the insights gained from each particular set of data within EDA, the results from the behavioural analysis prediction using any of the deep learning methods can add useful statistics to the e commerce companies. Understanding user behaviour Smart usability design engagement, site design optimization, personalisation and improvements in user experience..

Paper Citation

in Harvard Style

Sharath R., Kumar A., Sangameshwar B. and Sahoo B. (2025). Enhancing Customer Purchasing Behaviour Prediction in E- Commerce: A Deep Learning Perspective. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 649-655. DOI: 10.5220/0013599500004664

in Bibtex Style

@conference{incoft25,
author={Rekulara Sharath and Anishetty Vineeth Kumar and Bokkena Sangameshwar and Bidyutlata Sahoo},
title={Enhancing Customer Purchasing Behaviour Prediction in E- Commerce: A Deep Learning Perspective},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={649-655},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013599500004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Enhancing Customer Purchasing Behaviour Prediction in E- Commerce: A Deep Learning Perspective
SN - 978-989-758-763-4
AU - Sharath R.
AU - Kumar A.
AU - Sangameshwar B.
AU - Sahoo B.
PY - 2025
SP - 649
EP - 655
DO - 10.5220/0013599500004664
PB - SciTePress