Enhanced E-Commerce Sales Analysis with Deep learning Approach

Nowadays, in e-commerce market, Consumer's purchase decision is dependent on many different factors and it is an uncertain process. Using computer vision techniques and e-commerce marketing data, deep learning and Artificial Intelligent can be introduced for E-commerce content detection. Using Computer vision techniques, many valuable features can be extracted out from the e-commerce images, such as HSV color features, face detection, item detection, text detection, and image quality analysis. The relationship between variables provided valuable data and the relation between e-commerce images and sales are correlated in the e-commerce market. Furthermore, deep learning method and regression techniques were also used to determine consumers' preferences, and used to analyze the influencing factors. In this work, an end-to-end system was designed to extract e-commerce image information into quantitative data in consumer models, and proposed a comprehensive deep learning models which can improve consumers’ buying willingness.