Online auctions are proving themselves as a viable alternative in the C2C and B2C marketplace. Several thousand new items are placed for auction every day and determining which items to bid on or when and where to sell an item are difficult questions to answer for online-auction participants. This paper presents a multiagent Auction Advisor system designed to collect data related to online auctions and use the data to help improve the decision making of auction participants. A simulation of applied Auction Advisor recommendations and a small research study that used subjects making real purchases at online auctions both indicate that online-auction buyers and sellers achieve tangible benefit from the current information acquired by and recommendations made by the Auction Advisor agents.