Making conversations with chatbots more personalized

Many of the world's leading brands and increasingly government agencies are using intelligent agent technologies, also known as chatbots to interact with consumers. However, consumer satisfaction with chatbots is mixed. Consumers report frustration with chatbots arising from misunderstood quest...

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Bibliographic Details
Published in:Computers in human behavior Vol. 117; p. 106627
Main Authors: Shumanov, Michael, Johnson, Lester
Format: Journal Article
Language:English
Published: Elmsford Elsevier Ltd 01.04.2021
Elsevier Science Ltd
Subjects:
Chatbot
Chatbots
Consumers
Customer satisfaction
Customization
Human-computer interaction
Intelligent agents
Matching
Personality
Chatbot
Human-computer interaction
Personality
ISSN:0747-5632, 1873-7692
Online Access:Get full text
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Summary:Many of the world's leading brands and increasingly government agencies are using intelligent agent technologies, also known as chatbots to interact with consumers. However, consumer satisfaction with chatbots is mixed. Consumers report frustration with chatbots arising from misunderstood questions, irrelevant responses, and poor integration with human service agents. This study examines whether human-computer interactions can be more personalized by matching consumer personality with congruent machine personality using language. Although the idea that personality is manifested through language, and that people are more likely to be responsive to others with the same personality is well known, there is a dearth of research that examines whether this is consistent for human-computer interactions. Based on a sample of over 57,000 chatbot interactions, this study demonstrates that consumer personality can be predicted during contextual interactions, and that chatbots can be manipulated to ‘assume a personality’ using response language. Matching consumer personality with congruent chatbot personality had a positive impact on consumer engagement with chatbots and purchasing outcomes for interactions involving social gain. •Consumer personality can be predicted using machine learning.•Response language can be used to infer chatbot personality.•Matched consumer-chatbot personality improves sales and engagement.•Matching is most beneficial for socially important interactions.
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ISSN:0747-5632
1873-7692
DOI:10.1016/j.chb.2020.106627