The Internet and World Wide Web are becoming more and more dynamic in terms of their contents and usage. Agent-based shopping support (ASS) aims at keeping up with this dynamic environment by mimicking shoppers’ purchasing behavior in the electronic commerce transaction process in the sense of matching the profiles of web sites and shoppers. Evolutionary agent-based shopping supports are emerging as intelligent shopping support. This chapter contains the earliest attempt to gather and investigate the nature of current research. The idea of applying concepts of product characteristics from the matrix of Internet marketing strategies is introduced for solving problems of natural language information search. The process of focus-group research methodology is applied in acquiring the essential knowledge for examining shopper’s knowledge of search. An architecture of ASS in the case of outbound group package tour in Taiwan is presented. This work demonstrates the process of knowledge acquirement to tackle the problem of ineffective online information search by a customer-centric method.