Abstract
The aim of this paper is to compare online and offline retail price optimization and highlight the key differences. Online retail price optimization uses algorithms and data analysis to set the best price for an item on an e-commerce platform, considering product demand and competition. Offline retail price optimization involves manual methods, such as cost-plus pricing, market pricing, and psychological pricing, to price items in physical stores. The study involved a review of existing literature on retail price optimization and its application in online and offline retailing. The results showed that data availability is a significant difference between online and offline retail price optimization, with online retailers having access to more data. Online retailers can quickly adjust prices because of automation, while offline retailers need to manually change prices. The results of the study emphasize the importance of price optimization in both online and offline retailing and the benefits of using both methods together. The findings provide valuable insights for retail businesses and can inform future research in retail price optimization.
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