Authors:
Tim-Can Werning
1
;
María J. Escalona
2
and
Andreas Hinderks
3
Affiliations:
1
Department of Economics, Offenburg University of Applied Sciences, Germany
;
2
Department of Computer Science, University of Seville, Spain
;
3
Department of Economics and Computer Science, Hannover University of Applied Sciences and Arts, Germany
Keyword(s):
User Experience, Net Promoter Score, CSAT, Artificial Intelligence, Human-AI Interaction.
Abstract:
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.
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