Paper Contents
Abstract
The retail industry is a sizable and important sector of the economy made up of businesses that sell completed goods to consumers. The U.S. GDP (gross domestic output) is largely derived from retail sales. Brick & mortar shop sellers, who engage in the sale of goods from actual places so that customers can make purchases there, are where the business initially got its start. e-tailers, where commodities are advertised online and quickly delivered to clientsdoorsteps, have emerged over the past seven years. Online purchases make customerslives easier than ever because they might be made with the simple push of a mobile button. Although the internet era has made the retail sector more convenient, the day-to-day issues that retailers encounter across many sectors require more than just human foresight to be properly managed. and offer a viable solution that takes into account variables like cost, volume, and time. The use of statistics and machine learning models is pervasive and has successfully entered the retail industry as well. The current period's retail data is a priceless resource that is used as an input to these analytical models to produce practical knowledge for the retail businesses. The main issues facing the retail industry include client segmentation, inventory management, sales forecasting, and promotion tactics. Each of these issues is dissected to comprehend the potential outcomes, and then each is addressed with a solution that is statistically sound.
Copyright
Copyright © 2023 Dr. Neetu Anand . This is an open access article distributed under the Creative Commons Attribution License.
