Online chat encounters: Satisfying customers through dialogical interaction

Abstract

This research examines the effects of dialogical interaction within online chat (DIOC) on satisfaction, given the marketplace prevalence of these online customer–agent interactions and limited scholarly evidence about their impact. Drawing on service-dominant logic, person–environment fit theory, and existing dialogical interaction (DI) literature, the authors assess predictions using six experiments, including one on the live chat platform Slack, to demonstrate that DIOC significantly boosts satisfaction, especially among customers with utilitarian versus hedonic motives. This effect is explained by goal congruency. The authors also investigate boundary conditions where DIOC’s impact varies, finding it more beneficial for utilitarian-motivated customers when customer–agent similarity is low. Further, dialogical interaction with chatbots and human agents yields similar levels of customer satisfaction for utilitarian-motivated customers. In contrast, hedonically driven customers have higher levels of satisfaction when interacting with human agents. These findings offer practical implications for optimizing customers’ experiences in online chats.