The design and evaluation of an intelligent sales agent for online persuasion and negotiation

Online purchases from e-stores are getting popular among Internet users. Although many e-commerce activities, such as auctions, bargaining, and recommendation services are available, most e-stores lack clerk-like mechanisms to persuade potential buyers into buying products and to bargain with them for making a good deal. The objectives of this research are to design a lab prototype of a sales agent with persuasion and negotiation capabilities and to evaluate its effectiveness as a virtual clerk in an e-store. The prototypical intelligent sales agent (ISA) is equipped with reinforcement learning capabilities and an abstract argument framework. We conduct both laboratory and Internet experiments to assess ISA’s performance. The experimental results reveal that an e-store embedded within such a sales agent can improve a seller’s surplus and increase a buyer’s product valuation, willingness-to-pay, and satisfaction with the e-store.