Applying experimental online auctions in marketing research for multi-channel firms

Auction mechanisms allocate consumers’ demand revealing incentives. In this study, we highlight field experimental online auctions for their value in new product demand estimation. The immediate question is whether the information from online auctions can be utilized to get the full demand curve across various sales channels, since many firms utilize multi-channel strategies. Each channel may bear different transaction costs for its patrons. Hence, channel selection is the result of consumers’ self-selection based on transaction cost economics. Consequently, a consumer’s Willingness-To-Pay (WTP) in a selected channel reflects her/his depreciated pure WTP by the mixture of channel specific and individual-related characteristics determining transaction costs. We propose a skeleton model to resolve this self-selection bias, and this projects the partial demand observed in online auction channels to the whole demand curve. We discuss the kind of information that should be required to resolve this problem, and verify our approach using empirical testing. We demonstrate how online auction data, which firms have not yet capitalized on so far, can be a very valuable experimental resource for multi-channel firms’ marketing strategies.