Study Literature Review: Discovering the Effect of Chatbot Implementation in E-commerce Customer Service System Towards Customer Satisfaction

Abstract

Customer service plays a crucial role for a company. As an important aspect of e-commerce companies, they would be required to directly interact and try to solve customers’ problems that might occur anywhere and anytime. However, the limitation of human man hours became a barrier to overcome customers’ problems. On one hand, the rapid development of technology was predicted to replace the traditional human customer service with an Artificial Intelligence agent. On the other hand, this replacement affects the customer satisfaction. This paper performed a study literature review to discover the effect of chatbots and its impact towards customer satisfaction. In an e-commerce customer service use case, chatbots could be implemented in a number of methods. The methods implemented by chatbots are avatar-based, verbal-based, text-based, and menu-based. Research showed that text-based chatbot is the most commonly used methodology and has advanced the most, where some are implementing higher level machine learning methods, such as deep learning. The usage of such chatbot in e-commerce customer service systems will lower the cost but might also lower customer satisfaction, due to reasons such as unsatisfying answers and inhuman behavior. Research showed that even a more sophisticated chatbot doesn’t always mean higher customer satisfaction, even with high accuracy ratings. To look into customer satisfaction, this paper has identified 4 aspects of a chatbot that are relevant to customer satisfaction, which are privacy, reliability, personalization, and responsiveness. Chatbots currently excel in some of these quality measures, but require further research to effectively replace human customer service agents.