In: IWSDS 2021. International Workshop On Spoken Dialogue Systems Technology (IWSDS-2021) Springer 2021.
Abstract
In this paper, we analyze influencing factors for the assessment of user experience (UX) from a chatbot operating in the domain of technical customer support. To find out which UX factors can be assessed reliably in a crowdsourcing setup, we conduct a crowd-based UX assessment study through a set of scenario-based tasks and analyze the UX assessments in the light of influencing user characteristics, i.e., self-reported self-efficacy of individual users. By segmenting users according to self-efficacy, we find significant differences in UX assessment and expectations of users with respect to a series of UX constituents like acceptability, task efficiency, system error, ease of use, naturalness, personality and promoter score. Our results strongly suggest a potential application for essential personalization and user adaptation strategies utilizing self-efficacy for the personalization of technical customer support chatbots. Therefore, we recommend considering its influence when designing chatbot adaptation strategies for maximized customer experience.
@inproceedings{pub12045,
author = {
Cao, Yuexin
and
Carmona, Vicente Ivan Sanchez
and
Liu, Xiaoyi
and
Hu, Changjian
and
Iskender, Neslihan
and
Beyer, André
and
Möller, Sebastian
and
Polzehl, Tim
},
title = {On the Impact of Self-efficacy on Assessment of User Experience in Customer Service Chatbot Conversations},
booktitle = {IWSDS 2021. International Workshop On Spoken Dialogue Systems Technology (IWSDS-2021)},
year = {2021},
publisher = {Springer}
}
German Research Center for Artificial Intelligence Deutsches Forschungszentrum für Künstliche Intelligenz