Usability, Humanization, and Perceived Service are Predictors of Customer Satisfaction in Chatbot Interactions

Companies’ online presence has driven the use of chatbots in digital channels as a solution to expand customer service. These systems make it possible to offer satisfying experiences and handle requests on a large scale. Even when adopting this technology, companies must regularly assess whether these solutions increase or maintain customer satisfaction levels. This study analyzed the factors of humanization H, usability US, and perceived service quality QS in customer satisfaction when interacting with chatbots. Causal research is used to evaluate the relationships between the aforementioned factors and customer satisfaction using structural equation modeling (SEM). To this end, 423 people aged between 25 and 40 years were surveyed. The results confirm the five study hypotheses, establishing that H, US, and QS strongly, positively, and significantly influence user satisfaction when interacting with AI-driven chatbots. The study concludes that these factors are important in predicting customer satisfaction with online chatbots and that chatbot systems must be designed to generate satisfaction in terms of service quality and interaction. This study contributes a new understanding of the combined effect of the three factors by integrating them into a single model to explain satisfaction with online chatbot services.

AI-Driven chatbot; Anthropomorphism; Customer satisfaction; Chatbot usability; Perceived service quality

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