Merchandising/Marketing/Retailing: Management

Clicks or Text? How Customer Input Mode and Chatbots’ Response Accuracy Shape Customer Experience for Fashion Brands

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Abstract

As artificial intelligence (AI)-powered chatbots become integral to customer service in retail, it is essential to understand how chatbot features or design influence user experience. This paper proposes a conceptual model delineating how user input mode (click vs. text) and chatbot response accuracy (accurate vs. inaccurate) may shape customer satisfaction with chatbot interactions. Based on the expectancy violations theory (EVT), the model proposes that user input mode influences customers’ expectancy of chatbot performance in that consumers may have a higher expectation of chatbots that request click-based user inputs versus text-based user inputs. Therefore, accurate responses produce greater positive expectancy violations in text-based interactions, while inaccurate responses lead to stronger negative violations in click-based interactions. These expectancy violations, in turn, predict customer satisfaction. The proposed framework offers theoretical insights and practical implications for designing chatbot interfaces that balance performance accuracy and user expectations, encouraging future empirical validation.

 

Keywords: Chatbot, AI agent, Consumer, Artificial intelligence, Fashion, Brand

How to Cite:

Tawseef, T. & Kwon, W., (2025) “Clicks or Text? How Customer Input Mode and Chatbots’ Response Accuracy Shape Customer Experience for Fashion Brands”, International Textile and Apparel Association Annual Conference Proceedings 82(1). doi: https://doi.org/10.31274/itaa.21851