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Authors: Tim Polzehl 1 ; 2 ; Yuexin Cao 2 ; Vicente Ivan Sanchez Carmona 3 ; Xiaoyi Liu 3 ; Changjian Hu 3 ; Neslihan Iskender 2 ; André Beyer 4 and Sebastian Möller 1 ; 2

Affiliations: 1 German Research Center for Artificial Intelligence, Berlin, Germany ; 2 Technische Universität Berlin, Berlin, Germany ; 3 Lenovo Research AI Lab, Beijing, China ; 4 Crowdee GmbH, Berlin, Germany

Keyword(s): User Experience, Chatbot, Personalization, User Modeling, Information Savviness.

Abstract: Information savviness describes the ability to find, evaluate and reflect information online. Customers with high information savviness are more likely to look up product information online, read customer reviews before making a purchase decision. By assessing Information Savviness from chatbot interactions in a technical customer service domain, we analyze its impact on user experience (UX), expectations and preferences of the users in order to determine assessable personalization targets that acts dedicatedly on UX. To find out which UX factors can be assessed reliably, we conduct an assessment study through a set of scenario-based tasks using a crowd-sourcing set-up and analyze UX factors. We reveal significant differences in users’ UX expectations with respect to a series of UX factors 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 u ser adaptation strategies utilizing information savviness for the personalization of technical customer support chatbots. (More)

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Paper citation in several formats:
Polzehl, T.; Cao, Y.; Carmona, V.; Liu, X.; Hu, C.; Iskender, N.; Beyer, A. and Möller, S. (2022). Towards Personalization by Information Savviness to Improve User Experience in Customer Service Chatbot Conversations. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - HUCAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 36-47. DOI: 10.5220/0010814200003124

@conference{hucapp22,
author={Tim Polzehl. and Yuexin Cao. and Vicente Ivan Sanchez Carmona. and Xiaoyi Liu. and Changjian Hu. and Neslihan Iskender. and André Beyer. and Sebastian Möller.},
title={Towards Personalization by Information Savviness to Improve User Experience in Customer Service Chatbot Conversations},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - HUCAPP},
year={2022},
pages={36-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010814200003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - HUCAPP
TI - Towards Personalization by Information Savviness to Improve User Experience in Customer Service Chatbot Conversations
SN - 978-989-758-555-5
IS - 2184-4321
AU - Polzehl, T.
AU - Cao, Y.
AU - Carmona, V.
AU - Liu, X.
AU - Hu, C.
AU - Iskender, N.
AU - Beyer, A.
AU - Möller, S.
PY - 2022
SP - 36
EP - 47
DO - 10.5220/0010814200003124
PB - SciTePress

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