Don’t lose (type)face: Typeface Curvature and its effect on Customer Experience with Chatbots
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2022-08-23
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en
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Purpose - Advanced digital customer experiences are becoming a priority for modern companies. Chatbots is an AI-powered technology used to improve online customer service, by providing 24/7, fast, and high-quality services, enhancing customer satisfaction, and loyalty. While customers are becoming more and more familiar with visual communication, design-oriented studies focusing on chatbot interfaces are still limited. Additionally, the effect of the several aesthetic elements on customer experience has not been fully investigated. This study aimed to explore the effect of typography on customer experience with chatbots, in terms of hedonic and utilitarian value, on customer satisfaction and continuance intention to interact with the chatbot. The typographic design element that was investigated was typeface curvature.
Design & Methodology - This study used an online experiment 2×2 between-subjects design, followed by a questionnaire to explore participants’ perceptions of Hedonic Value, Utilitarian Value, Customer Satisfaction, and Continuance Intention.
Results - ANCOVA and multiple regression analysis were conducted to analyze the data derived from 324 participants. Based on the results, there is no effect of typefaces on customer experience, which means that typeface curvature does not influence how people perceive chatbots. Second, there is a significant effect from the context on customer experience through the hedonic value. Third, the factors that significantly influence how people experience chatbots, are the attitude towards chatbots, the mood before the interaction, and their age. Finally, customer satisfaction and continuance intention to use a chatbot in the future can be predicted by the two aspects of customer experience.
Discussion - The use of any sans-serif typeface in the chatbot context does not influence customer experience. The context-related risk can influence in a negative way customer experience, by eliminating hedonic value. Thus, in a service context with high levels of perceived risk hedonic value should be enhanced in alternative ways. Attitudes towards technology, customers’ moods before the interaction with a chatbot, and age should be considered by the chatbot designers as they significantly contribute to customers’ perceptions of the chatbot. Customer satisfaction and customers’ intention to continue the interaction with the chatbot in the future can be predicted by the quality of customer experience. These results can be particular for anyone interested in chatbots, researchers, chatbot designers, UX/UI designers, and customer experience managers.
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Faculteit der Managementwetenschappen