Implementation Chatbot for SMEs Using Artificial Intelligence Markup Language to Improve Customer Integration and Business Performance

Abstract

Chatbots have been extensively adopted to produce more positive customer experiences as customers now spend more time in digital surroundings. Despite the technological advancement and benefits of chatbots for client service, exploration of chatbot operations for small and medium-sized enterprises (SMEs) is limited. The absence of exploration explaining the struggles faced by SMEs contributes to the gap in SMEs’ chatbot adoption. This exploration determines the features and rudiments that fit with SMEs’ characteristics and their guests' interactions with chatbots. A mixed-methods approach is used to understand SMEs’ needs. The first study uses interviews with SME business owners and their customers in order to explore the features that chatbots should offer for SME by identifying combinations between chatbots' generic features and SMEs' customer characteristics. The second study tests features identified in SMEs customers to empirically test featured chatbots’ influence on anthropomorphism, perceived enjoyment, perceived ease of use, perceived usefulness, and how they affect SMEs’ customer intentions to use chatbots and their shopping intentions. This paper contributes to the emerging service literature on the use of chatbots for service interactions, particularly for SMEs using Artificial Intelligence Markup Language. The data that has been obtained was analyzed using a Likert scale. As a result, the accuracy of using Artificial Intelligence Markup Language is 84.8%.