An In-depth Analysis of Global Online Retail Sales Using the Classical Apriori Algorithm

Abstract

In today's retail and product sales world, firms rely heavily on customer behavior information to make business decisions. Also, e-commerce giants and other businesses rely on this data to improve customer service and increase profits. Customer service is being improved by vendors, who will no longer waste time searching for products and instead share and promote the peripheral or the product which is most commonly purchased with the primary product. For example, we utilized an apriori algorithm to determine whether or not it was possible to purchase a B-post in conjunction with an A-post. It offers a number of advantages. Shopping on a portal or at a store for a short period of time enhances the rating of the portal and the site's performance.