In pay-per-bid auctions, placing a bid costs a fee, and only raises the price of the item by a small increment. At the conclusion of the auction, the last bidder wins, and the price paid by the winning bidder is subsidised by the bidding fees paid by unsuccessful bidders. In this short paper, the first publicly available analytics of data from a pay-per-bid website are presented. We present a visual analysis approach using a specific tool developed for the purpose. This dataset represents a difficult challenge because it is huge, it is difficult to evaluate in practice even
using auction theory since there exists no mathematically optimal strategy for successful bidding, and non-trivial patterns are sought.