Abstract
When talking about products, people often express their needs in vague terms with vocabulary that does not necessarily overlap with product descriptions written by retailers. This poses a problem for chatbots in online shops, as the vagueness and vocabulary mismatch can lead to misunderstandings. In human-human communication, people intuitively build a common understanding throughout a conversation, e.g., via feedback loops. To inform the design of conversational product search systems, we investigated the effect of different feedback behaviors on users’ perception of a chatbot’s competence and conversational engagement. Our results show that rephrasing the user’s input to express what was understood increases conversational engagement and gives the impression of a competent chatbot. Using a generic feedback acknowledgment (e.g., “right” or “okay”), however, does not increase engagement or perceived competence. Auto-feedback for conversational product search systems therefore needs to be designed with care.
Original language | English |
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Title of host publication | CUI '23 |
Subtitle of host publication | Proceedings of the 5th International Conference on Conversational User Interfaces |
Editors | Minha Lee, Cosmin Munteanu, Martin Porcheron, Johanne Trippas, Sarah Theres Völkel |
Publisher | Association for Computing Machinery |
Number of pages | 5 |
ISBN (Electronic) | 979-8-4007-0014-9 |
DOIs | |
Publication status | Published - 19 Jul 2023 |
Event | 5th International Conference on Conversational User Interfaces, CUI 2023 - Eindhoven, Netherlands Duration: 19 Jul 2023 → 21 Jul 2023 Conference number: 5 |
Conference
Conference | 5th International Conference on Conversational User Interfaces, CUI 2023 |
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Abbreviated title | CUI 2023 |
Country/Territory | Netherlands |
City | Eindhoven |
Period | 19/07/23 → 21/07/23 |
Keywords
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