Smart Recommendations in E-commerce: A Business Intelligence Approach for Personalized Customer Engagement and Increased Sales

Salah-ddine Krit

Ibn Zohr University, Agadir, Morocco  

Email: salahddine.krit@gmail.com

Abstract

 The e-commerce industry is continuously growing, and personalized customer engagement has become a crucial aspect of business success. In this paper, we propose a smart recommendation system using a business intelligence approach to enhance customer engagement and increase sales. We explore the use of machine learning algorithms to generate personalized product recommendations, incorporating customer behavior analysis and historical data. Our proposed approach considers various factors such as purchase history, browsing history, demographics, and social media activities to generate personalized recommendations. The system's effectiveness is evaluated using metrics such as click-through rate, conversion rate, and revenue generated. We believe that our proposed approach can provide e-commerce businesses with an effective way to increase customer engagement and sales while improving the overall customer experience.

Keywords: E-Commerce; Business Intelligence; Recommendation System; Customer Engagement