AI SearchInfluencing customer preferences to achieve sales objectives
Call Number: AIT Thesis no.IM-09-06 Material type:
SeriesSeries: Asian Institute of Technology. Thesis ; no. IM-09-06Publication details: Pathum Thani, Thailand : Asian Institute of Technology, 2009Description: 53 p. : ill. + 1 online resourceSubject(s): Online resources: Dissertation note: Thesis (M.Eng.) - Asian Institute of Technology, 2009 Summary: Online shopping is one of the most popular applications in the Internet. Current online shopping systems usually employ recommendation technologies to assist customers in choosing the best product based on their preferences. However, most of recommendation systems are neutral. They do not have their own utility and only focus on how to effectively elicit the customer{u2019}s preferences, not how to affect them. Recent results in customer behavior and decision analysis research have shown that the customer{u2019}s preferences are actually constructive and thus can be influenced. This thesis works on how to design a self-interested automatic sales agent that can influence the customer{u2019}s preferences to maximize its utility. A general framework for such a capability was proposed and a prototype was built to evaluate the framework. The evaluation results showed that our sales agent can achieve on average higher utility than that of normal recommendation systems while getting the same customer{u2019}s average utility and satisfaction level.
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A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Information Management, School of Engineering and Technology
Thesis (M.Eng.) - Asian Institute of Technology, 2009
Online shopping is one of the most popular applications in the Internet. Current online shopping systems usually employ recommendation technologies to assist customers in choosing the best product based on their preferences. However, most of recommendation systems are neutral. They do not have their own utility and only focus on how to effectively elicit the customer{u2019}s preferences, not how to affect them. Recent results in customer behavior and decision analysis research have shown that the customer{u2019}s preferences are actually constructive and thus can be influenced. This thesis works on how to design a self-interested automatic sales agent that can influence the customer{u2019}s preferences to maximize its utility. A general framework for such a capability was proposed and a prototype was built to evaluate the framework. The evaluation results showed that our sales agent can achieve on average higher utility than that of normal recommendation systems while getting the same customer{u2019}s average utility and satisfaction level.
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