Linking User Experience and Business Outcomes: How Perceived Usefulness of AI Chatbots Predicts Satisfaction and NPS

The integration of AI-based features is rapidly transforming interactions with software systems. While these innovations aim to enhance functionality, their impact on user experience and business outcomes such as satisfaction and loyalty remains underexplored. This study investigates how the user experience (UX) of AI chat bots relates to two key user-level outcomes: Customer Satisfaction (CSAT) and Net Promoter Score (NPS). Drawing on a sample of N = 146 users, we conducted regression analyses, including interaction terms with AI usage frequency and perceived competency. Results indicate that perceived Usefulness significantly predicts both CSAT and NPS, with partial support of moderation effect by the frequency of AI use. Specifically, higher usage increases the positive impact of Usefulness on NPS. Overall, our regression models for CSAT and NPS explained around 39% and 48% of the variance, respectively. These results indicate a good model fit and underline the importance of good UX in AI systems, as this is significantly impacting the satisfaction and loyalty of users. In summary, by linking established UX metrics to strategic business indicators, we show how UX professionals can contribute to more business value and additionally offer guidance to adopt a more user-centered perspective on AI development.