Unveiling Customer Expectations of Chatbot Interactions: A Systematic Literature Review and Research Agenda

Abstract

Chatbots have become pivotal in communications between the customer and the organization, offering continuous support by promptly addressing queries. However, despite their prevalence, many customers report unsatisfactory experiences. This study addresses this issue by conducting a systematic literature review that aims to identify and analyze customer expectations of chatbot interactions. Incorporating insights from 91 studies, our review reveals that the literature predominantly focuses on customer perceptions, or post-experience evaluations, rather than pre-interaction expectations. Leveraging existing categorizations, we present a conceptual framework that identifies two overarching dimensions of pre-interaction expectations: functional and experiential. We explore factors shaping these expectations, highlighting personal and situational influences. Our analysis highlights the complex ways in which different expectations combine to shape how customers interact with chatbots. Drawing on these insights, we propose a research agenda that outlines key gaps and future directions to advance understanding of customer expectations in AI-mediated service contexts.

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