Developing an eCommerce Pricing Model Using Rank Centrality

Abstract

In recent years, eCommerce websites have become a popular alternative to traditional marketplaces, providing convenience to customers to order products from home and have them shipped. As a result, competition between sellers on the eCommerce websites has intensified in recent years, making a pricing strategy necessary to perform well in this marketplace.

This paper attempts to model eCommerce competition between different sellers using the principle of Rank Centrality, and uses neural networks to accurately predict the winning seller on eCommerce websites, such as Amazon, based on factors including pricing, seller rating, and shipping guarantees for each seller. Using this prediction, a pricing strategy is formed to maximize sales volume and profits on these sites. This strategy is then implemented and evaluated as part of a 6-month internship with Spero Goods.