The Influence of Message Direction on Attribute Benefit and Purchase Intention Applied to the Logical Design of an AI Chatbot

Abstract

This study aims to explore the influence of various possible combinations of consumer attribute benefits and the message direction provided by merchants on the final purchase intention of consumers. A two-factor experimental design was used to collect data from Generation Z consumers. Four experimental combination scenarios were designed based on consumer attribute benefits (hedonic or utilitarian) and message direction (positive or negative messages). A total of 160 valid samples were obtained, and the influence of variable-final purchase intention was analyzed. The results showed that the combination of product attributes and message direction has a significant impact on purchase intention and that hedonic products should be recommended to process-benefit consumers through positive messages. However, chatbots should choose utilitarian products and negative messages to effectively improve consumers’ purchase intention and willingness. In practical application, by finding out the best correspondence method of message transmission and providing the AI chatbot with a reference for the logical construction of content transmission, the communication efficiency between merchants and consumers can be enhanced, and the scientific and technological service capability of merchants can be improved.