Understanding the user satisfaction and loyalty of customer service chatbots

The artificial intelligence (AI) chatbot is emerging as a significant corporate customer-facing application, potentially increasin customer service efficiency while reducing costs. However, little work has sought to assess the quality of service they provide consumers. This study applies the e-service quality by incorporating conversational AI quality to predict users' satisfaction and loyalty to customer service chatbots. The proposed model was empirically evaluated using survey data collected from 219 users responding about their perceptions of customer service chatbots. The findings indicate that AI chatbot service recovery quality and AI chatbot conversational quality significantly influence user satisfaction. On the other hand, core AI chatbot service quality and satisfaction significantly influenced chatbot user loyalty. This study contributes to researchers and practi-tioners by proposing and evaluating a more comprehensive chatbot e-service quality that combines both fundamental (core service and service recovery qualities) and human-like (conversational quality) aspects of e -service. The results are of value in devising future AI chatbot services and related strategies.

Automated summary

This study evaluates the e-service quality of chatbots by incorporating conversational AI quality, and finds that service recovery quality and conversational quality significantly affect user satisfaction, while core service quality and satisfaction significantly influence user loyalty. The findings have implications for the development of future AI chatbot services and related strategies.