Sensory-Marketing-Evaluation of E-Commerce Websites with Artificial Intelligence

Abstract

Multisensory consumer engagement on e-commerce websites is technically limited to visual, acoustic, and written elements. Consumers communicate, buy, and share products and services via digital environments in which sensory information is limited. To improve consumers' online sensory experience, media types and the content need to be quantitatively assessed and adapted. This project aims to develop a quantitative model, an Online Sensory Marketing Index (OSMI), which assesses ecommerce websites in multisensory communication quality. The OSMI will be supported by an automatic procedure that is based on artificial intelligence. Content of texts, images, and videos is evaluated by natural language processing (NLP), natural language generation (NLG) as well as automatic machine learning (AutoML) procedures. Multiple e-commerce websites from various industries are examined.