Dynamic Price Optimization for Ecommerce Platform

G. Uma Bhargavi, M. Balakrishna, H. Shivani, B. Bramhani, D. Pavithra

2025

Abstract

An adaptable price adjustment system plays a vital role in developing both e-commerce platform revenues and interaction with customers. The research adopts an original AI- based strategy to optimize pricing systems. The solution merges several operational functions that allow real-time price changes as well as reinforcement learning-based optimization of prices and competitive pricing analysis and market demand forecasting capabilities. The model employs automatic price mechanisms that adjust product costs in response to customer interactions and market demand as well as competitive rate alterations by using ML and DL techniques for integration. Through experimental tests reinforcement learning-based pricing methods generated an 18% increase of revenue together with 10.2% growth in customer conversion and delivered 13% better profit margin results. The e-commerce platform provides large companies with a flexible real- time pricing system that operates rapidly. Through the research evaluation it is shown that AI-based price strategies create a maximized market position and boost long-term profit while maintaining fair prices across market changes.

Paper Citation

in Harvard Style

Bhargavi G., Balakrishna M., Shivani H., Bramhani B. and Pavithra D. (2025). Dynamic Price Optimization for Ecommerce Platform. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 18-23. DOI: 10.5220/0013907300004919

in Bibtex Style

@conference{icrdicct`2525,
author={G. Bhargavi and M. Balakrishna and H. Shivani and B. Bramhani and D. Pavithra},
title={Dynamic Price Optimization for Ecommerce Platform},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={18-23},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013907300004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Dynamic Price Optimization for Ecommerce Platform
SN - 978-989-758-777-1
AU - Bhargavi G.
AU - Balakrishna M.
AU - Shivani H.
AU - Bramhani B.
AU - Pavithra D.
PY - 2025
SP - 18
EP - 23
DO - 10.5220/0013907300004919
PB - SciTePress