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.
|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|
|Number of pages||15|
|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
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|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|
|Period||19/7/26 → 19/7/31|
Bibliographical noteFunding Information:
Acknowledgements. This research was supported by Korea Institute for Advancement of Technology (KIAT) Grant funded by the Korea Government (MOTIE) (N0001436, The Competency Development Program for Industry Specialist).
© 2019, Springer Nature Switzerland AG.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)