OPTIMIZING ONLINE RETAIL PROFITS: A COMPARATIVE ANALYSIS OF DATA-DRIVEN DYNAMIC PRICING MODELS

Authors

  • N. Prakasha Assistant Professor of Commerce, Government Women’s College, Kolar, Karnataka

Keywords:

Dynamic Pricing, Data-Driven Strategies, Online Retail, Comparative Analysis, Customer Satisfaction, Revenue Generation, E-Commerce Pricing Models

Abstract

The dynamic landscape of online retail, optimizing pricing strategies has emerged as a critical determinant of business success. This research article explores the fascinating realm of data-driven pricing strategies in online retail, embarking on a journey through the intricacies of dynamic pricing models. With a keen focus on three distinct approaches—dynamic pricing, surge pricing, and personalized pricing—we aim to unravel the profound impact these strategies wield on sales figures, customer satisfaction, and overall revenue generation.

Our exploration begins by delving into the historical evolution of dynamic pricing within the e-commerce sphere. We traverse the path of data-driven strategies and their undeniable significance in shaping pricing decisions. An extensive review of existing literature further illuminates the multifaceted nature of these pricing models.

The heart of our study lies in the methodology, where we meticulously detail our data collection and analysis techniques. Employing a rigorous approach, we compare and contrast the three pricing models, dissecting their influence on the variables that matter most to businesses: sales volume, customer satisfaction levels, and the bottom line. Statistical methods are deftly wielded to unearth patterns, trends, and correlations within the data.

With a rich tapestry of empirical evidence in hand, our discussion section interprets these findings in a broader context. We weigh the strengths and weaknesses of each pricing model, offering valuable insights for online retailers seeking to optimize their pricing strategies. While we acknowledge certain study limitations, we also chart a course for future research avenues in this dynamic field.

This research article contributes a fresh perspective on the nexus between data-driven pricing strategies and the success of online retail ventures. Our findings resonate with the e-commerce industry, underscoring the pivotal role these strategies play in navigating the ever-changing consumer landscape.

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Additional Files

Published

15-09-2023

How to Cite

N. Prakasha. (2023). OPTIMIZING ONLINE RETAIL PROFITS: A COMPARATIVE ANALYSIS OF DATA-DRIVEN DYNAMIC PRICING MODELS. International Education and Research Journal (IERJ), 9(9). Retrieved from http://ierj.in/journal/index.php/ierj/article/view/3065