Group-buying ads seeking a minimum number of customers before the deal expiry are increasingly used by the daily-deal providers. Unlike the traditional web ads, the advertiser's profits for group-buying ads depends on the time to expiry and additional customers needed to satisfy the minimum group size. Since both these quantities are time-dependent, optimal bid amounts to maximize profits change with every impression. Consequently, traditional static bidding strategies are far from optimal. Instead, bid values need to be optimized in real-time to maximize expected bidder profits. This online optimization of deal profits is made possible by the advent of ad exchanges offering real-time (spot) bidding. To this end, we propose a real-time bidding strategy for group-buying deals based on the online optimization of bid values. We derive the expected bidder profit of deals as a function of the bid amounts, and dynamically vary bids to maximize profits. Further, to satisfy time constraints of the online bidding, we present methods of minimizing computation timings. Subsequently, we derive the real time ad selection, admissibility, and real time bidding of the traditional ads as the special cases of the proposed method. We evaluate the proposed bidding, selection and admission strategies on a multi-million click stream of 935 ads. The proposed real-time bidding, selection and admissibility show significant profit increases over the existing strategies. Further the experiments illustrate the robustness of the bidding and acceptable computation timings.
The group-buying auction is a new kind of dynamic pricing mechanism on the Internet. It is a variant of the sellers' price double auction, which makes the bidders as a group through Internet to get the volume discounts, i.e., the more bidders bid, the lower the price of the object being auctioned becomes. In this paper, we analyze the group-buying auction under some assumptions, such as that the independent private values (IPVs) model applies and bidders are risk neutral and symmetric, etc., and build an incomplete information dynamic game model to illustrate the bidders' bidding process. It proves that for the bidders there exists a weakly dominant strategy S, i.e., no matter when a bidder arrives at the auction and what the bidding history is, the highest permitted bid price that is no greater than his value to the object is always his optimal bid price but may not be the unique one. Web-based group-buying mechanisms are being widely used for both business-to-business (B2B) and business-to-consumer (B2C) transactions. We survey currently operational online group-buying markets, and then study this phenomenon using analytical models. We build on the literatures in information economics and operations management in our analytical model of a monopolist offering Web-based group-buying under different kinds of demand uncertainty. We derive the monopolist's optimal group-buying schedule under varying conditions of heterogeneity in the demand regimes, and compare its profits with those that obtain under the more conventional posted-price mechanism. We further study the impact ofproduction postponement by endogenizing the timing of the pricing and production decisions in a two-stage game between the monopolist and buyers. Our results have implications for firms' choice of price-discovery mechanisms in e-markets, and for the scheduling of production and pricing decisions in the presence (and absence) of scale economies of production.