A Data-Driven Design Framework for Customer Service Chatbot

Shinhee Hwang; Beomjun Kim; Keeheon Lee

doi:10.1007/978-3-030-23570-3_17

A Data-Driven Design Framework for Customer Service Chatbot

Shinhee Hwang, Beomjun Kim, Keeheon Lee

Techno-Art Division

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Citations (Scopus)

Abstract

User experience in customer service is critical. It is because customer service is what a customer first requests for a service. The service fails to satisfactory response will cause a crucial damage. Albeit business includes a chatbot for better responsiveness, customization is still necessary to fulfill the satisfaction from customer service. For customization, a designer performs qualitative research such as surveys, self-reports, interviews, and user observation to pull out key characteristics and to build personas based on the characteristics. However, a small sample size and cognitive limitation of a researcher demand more data to model persona better. Therefore, in this study, we introduce a data-driven framework for designing customer service chatbot that utilizes the past customer behavior data from clickstreams and a customer service chatbot. We apply this framework to a cartoon streaming service, Laftel. In result, we generate three types of customer service chatbots for three personas such as explorer, soft user, and hard user. In the future, we will validate our result by conducting a field experiment.

Original language	English
Title of host publication	Design, User Experience, and Usability. Design Philosophy and Theory - 8th International Conference, DUXU 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings
Editors	Aaron Marcus, Wentao Wang
Publisher	Springer Verlag
Pages	222-236
Number of pages	15
ISBN (Print)	9783030235697
DOIs	https://doi.org/10.1007/978-3-030-23570-3_17
Publication status	Published - 2019
Event	8th International Conference on Design, User Experience, and Usability, DUXU 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019 - Orlando, United States Duration: 2019 Jul 26 → 2019 Jul 31

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11583 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Design, User Experience, and Usability, DUXU 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019
Country/Territory	United States
City	Orlando
Period	19/7/26 → 19/7/31

Bibliographical note

Publisher Copyright:
© 2019, Springer Nature Switzerland AG.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-23570-3_17

Cite this

Hwang, S., Kim, B., & Lee, K. (2019). A Data-Driven Design Framework for Customer Service Chatbot. In A. Marcus, & W. Wang (Eds.), Design, User Experience, and Usability. Design Philosophy and Theory - 8th International Conference, DUXU 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings (pp. 222-236). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11583 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-23570-3_17

Hwang, Shinhee ; Kim, Beomjun ; Lee, Keeheon. / A Data-Driven Design Framework for Customer Service Chatbot. Design, User Experience, and Usability. Design Philosophy and Theory - 8th International Conference, DUXU 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. editor / Aaron Marcus ; Wentao Wang. Springer Verlag, 2019. pp. 222-236 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "User experience in customer service is critical. It is because customer service is what a customer first requests for a service. The service fails to satisfactory response will cause a crucial damage. Albeit business includes a chatbot for better responsiveness, customization is still necessary to fulfill the satisfaction from customer service. For customization, a designer performs qualitative research such as surveys, self-reports, interviews, and user observation to pull out key characteristics and to build personas based on the characteristics. However, a small sample size and cognitive limitation of a researcher demand more data to model persona better. Therefore, in this study, we introduce a data-driven framework for designing customer service chatbot that utilizes the past customer behavior data from clickstreams and a customer service chatbot. We apply this framework to a cartoon streaming service, Laftel. In result, we generate three types of customer service chatbots for three personas such as explorer, soft user, and hard user. In the future, we will validate our result by conducting a field experiment.",

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Hwang, S, Kim, B & Lee, K 2019, A Data-Driven Design Framework for Customer Service Chatbot. in A Marcus & W Wang (eds), Design, User Experience, and Usability. Design Philosophy and Theory - 8th International Conference, DUXU 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11583 LNCS, Springer Verlag, pp. 222-236, 8th International Conference on Design, User Experience, and Usability, DUXU 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019, Orlando, United States, 19/7/26. https://doi.org/10.1007/978-3-030-23570-3_17

A Data-Driven Design Framework for Customer Service Chatbot. / Hwang, Shinhee; Kim, Beomjun; Lee, Keeheon.
Design, User Experience, and Usability. Design Philosophy and Theory - 8th International Conference, DUXU 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. ed. / Aaron Marcus; Wentao Wang. Springer Verlag, 2019. p. 222-236 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11583 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Kim, Beomjun

AU - Lee, Keeheon

PY - 2019

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N2 - User experience in customer service is critical. It is because customer service is what a customer first requests for a service. The service fails to satisfactory response will cause a crucial damage. Albeit business includes a chatbot for better responsiveness, customization is still necessary to fulfill the satisfaction from customer service. For customization, a designer performs qualitative research such as surveys, self-reports, interviews, and user observation to pull out key characteristics and to build personas based on the characteristics. However, a small sample size and cognitive limitation of a researcher demand more data to model persona better. Therefore, in this study, we introduce a data-driven framework for designing customer service chatbot that utilizes the past customer behavior data from clickstreams and a customer service chatbot. We apply this framework to a cartoon streaming service, Laftel. In result, we generate three types of customer service chatbots for three personas such as explorer, soft user, and hard user. In the future, we will validate our result by conducting a field experiment.

AB - User experience in customer service is critical. It is because customer service is what a customer first requests for a service. The service fails to satisfactory response will cause a crucial damage. Albeit business includes a chatbot for better responsiveness, customization is still necessary to fulfill the satisfaction from customer service. For customization, a designer performs qualitative research such as surveys, self-reports, interviews, and user observation to pull out key characteristics and to build personas based on the characteristics. However, a small sample size and cognitive limitation of a researcher demand more data to model persona better. Therefore, in this study, we introduce a data-driven framework for designing customer service chatbot that utilizes the past customer behavior data from clickstreams and a customer service chatbot. We apply this framework to a cartoon streaming service, Laftel. In result, we generate three types of customer service chatbots for three personas such as explorer, soft user, and hard user. In the future, we will validate our result by conducting a field experiment.

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Hwang S, Kim B, Lee K. A Data-Driven Design Framework for Customer Service Chatbot. In Marcus A, Wang W, editors, Design, User Experience, and Usability. Design Philosophy and Theory - 8th International Conference, DUXU 2019, Held as Part of the 21st HCI International Conference, HCII 2019, Proceedings. Springer Verlag. 2019. p. 222-236. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-23570-3_17

A Data-Driven Design Framework for Customer Service Chatbot

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