The effect of non-facial emojis-text congruency on user satisfaction in chatbot interactions

Abstract Improving human–chatbot communication requires understanding how different design elements can make interactions clearer and more effective. This research examines emoji–text congruency as one mechanism that enhances user satisfaction in chatbot interactions. Across two experiments conducted in the travel (Study 1) and healthcare (Study 2) domains, we show that when emojis are semantically aligned with the accompanying text, users perceive the chatbot as more competent, which in turn increases satisfaction. To isolate this effect from anthropomorphic influences, the studies focus on non-facial emojis, which convey meaning without mimicking human expressions, thus avoiding potential discomfort associated with excessive human-likeness. However, the positive effect of congruency weakens when the chatbot adopts an overly informal language style. These findings highlight the importance of integrating visual and verbal cues coherently to improve user experience and inform the design of effective, professional virtual assistants.