Abstract
In the past few years, customers' buying habits have changed a lot because of e-commerce. E-commerce systems have a lot of benefits over traditional ways of selling things in stores because they can be changed to fit the wants and tastes of each user. Personalizing these experiences has the ability to make customers happier, which could increase sales and make platforms more successful. In sales of things like computers, users often put together a product based on its parts in a way that suits their personal tastes. To successfully plan inventory management, pricing strategies, and marketing efforts, it is very important to be able to correctly predict which product combinations will be the most popular. This position paper is focusing on how to build a decision support system software that can predict the likelihood of a buy for product baskets that are put together on the fly. The main goal of this decision support system software is to help e-commerce companies better understand what customers want and adjust their tactics to meet those needs. By designing, building and using this software, e-commerce companies can learn more about how their customers behave and increase their sales.