Comparison shopping agent
 | It has been suggested that this article be merged into Price comparison service. (Discuss) Proposed since August 2011. |
Comparison shopping agents, also called shopbots,[1][2] are web-based intelligent software applications that help online shoppers find lower prices for commodities or services. Price comparison services were the earliest services provided by comparison shopping agents. To search the price of a particular item, a comparison shopping agent searches multiple online stores or feeds based on user-provided keywords or context.
The first widely recognized comparison-shopping agent was BargainFinder developed by then Andersen Consulting (now Accenture) and its SmartStore center in 1995 for an experiment.
The first commercial shopping agent, called Jango, was produced by Netbot, a Seattle startup company founded by University of Washington professors Oren Etzioni and Daniel S. Weld; Netbot was acquired by the Excite portal in late 1997. Junglee, a Bay-area startup, also pioneered comparison shopping technology and was soon acquired by Amazon.com. Other early comparison shopping agents included pricewatch.com and killerapp.com. Most of them were price comparison for computer related products and hence did not attract much public attention.
In the early development stage from 1995 to 2000, comparison shopping agents included not only price comparison but also rating and review services for online vendors and products. For example, services like Bizrate.com provided ratings for online vendors. Today, websites like Epinion.com provide review and rating services for products. Altogether, there were three broad categories of comparison shopping services.[3]
Later, through mergers and acquisitions, many services were consolidated. As a result, shopping.com, PriceGrabber and shopzilla have become the top three comparison shopping agents since 2000.
Comparison shopping agents may be considered early examples of the Semantic Web, but early systems used wrappers to extract structured information about products from Web pages. Wrapper construction requires extensive programming and results in a fragile system, since they need to be reprogrammed when an online store changes its layout. Modern comparison shopping systems get most of their data from relational data feeds generated by retailers. While this typically yields more robust results, it requires retailer cooperation and may produce less comprehensive listings.
Partial List of Comparison Shopping Agents
References
- ^ Doorenbos, B; Etzioni, O; Weld, D. A scalable comparison-shopping agent for the World-Wide Web, AGENTS '97 Proceedings of the first international conference on Autonomous agents ACM New York, NY, USA 1997
- ^ Clark, D. Shopbots become agents for business change, IEEE Computer, Vol. 33, Issue 2, 2000
- ^ Wan, Y., Menon, S. and Ramaprasad, A. A Classification of Product Comparison Agents, 2003