Abstract: Due to the huge amount of data available to buyers, the use of sophisticated algorithms can increase the revenue of ecommerce stores with modern recommender systems. The study was designed to investigate the impact of recommender systems on e-buyers online purchasing behaviors, and predict purchase patterns of buyers. The result of the study revealed how recommender systems affect shopping experience, increase sales for business owners and reach efficient product stocking and delivery. This research proposes an approach of increase in sales and the possibility of purchase prediction based on recommender systems. A survey of e-buyers was taken to determine the impact of recommender systems on past and future purchases. Results show that recommender systems improve shopping experience, increase purchase and can be a good tool to remind buyers of what they need to buy. It shows that recommender systems have the ability to predict what a buyer may be interested in purchasing. Based on the obtained user behavior and e-buyers satisfaction with recommender systems, e commerce stores can take advantage of this to send personalized recommended items to buyers’ emails to increase their sales. As e commerce shopping becomes more accepted globally, findings in this study have benefits to both shopping experience and sales enhancement.Abstract: Due to the huge amount of data available to buyers, the use of sophisticated algorithms can increase the revenue of ecommerce stores with modern recommender systems. The study was designed to investigate the impact of recommender systems on e-buyers online purchasing behaviors, and predict purchase patterns of buyers. The result of the study reveal...Show More
