Customer behavior in the presence of algorithmic marketing agents: The role of hedonic values

Artificial intelligence (AI) marketing agents have increasingly emerged as a viable alternative to human representatives for direct customer interactions. In this research, we investigated customer behaviors in response to sales scenarios managed by AI agents considering individual customers' values. In three pre-registered studies, we examined the willingness of 1417 participants to engage in promotional activities related to purchasing real estate and vehicles. Using regression and simple slope analyses, we examined how the interaction among agents (human or algorithm), response types (negative or positive), and customers' hedonic values influence the likelihood of becoming promoters. Our results revealed a moderation effect in which the relationship between the type of marketing agent and the response type was influenced by customers' hedonic values. We found a positive relationship between hedonic values and promotion behavior when negative feedback was delivered by a human agent and when positive feedback came from an algorithmic agent. In contrast, algorithmic agents tend to elicit flatter responses across hedonic levels when delivering negative feedback, indicating reduced emotional engagement but also less potential for dissatisfaction. These insights emphasize the importance of aligning the source of communication with individual consumer characteristics to enhance customer promotion.