Implementing Big Data Analytics in E-Commerce: Vendor and Customer View

Abstract

Due to the information revolution, one of the biggest challenges of e-commerce is the huge data that needs to be processed and analyzed to gain benefits from it. Big Data Analytics (BDA) aims to improve the decision-making process by analyzing and understanding big data, e.g., messages, social media posts, etc. Furthermore, BDA capabilities are used in e-commerce activities as a key growth direction to increase vendors’ revenues and attract customers. Based on the importance of analyzing big data and its advantages to e-commerce operations, this paper aims to study the values of implementing BDA in e-commerce to both vendors and consumers. Fifteen papers are selected to analyze the impacts of analyzing big data in e-commerce. Electronic vendors (E-vendors) use BDA to gain the competitive advantages they need to understand consumer behaviour and increase their income by improving customer loyalty. Besides, recommendation systems derived from BDA personalize the searching and shopping experience of the customers. However, there are some negative effects derived from applying BDA in e-commerce, such as shopping addiction. In addition, e-vendors have to deal with expensive BDA tools and professionals. In conclusion, even though BDA enhances consumers’ and vendors’ electronic shopping experience, the rapid growth of data is still challenging.

Keywords

• Big data analytics (BDA)
• E-commerce
• predictive analytics
• customization
• increase revenues