Group-buying ads seeking a minimum number of customers before the deal expiryare increasingly used by the daily-deal providers. Unlike the traditional webads, the advertiser's profits for group-buying ads depends on the time toexpiry and additional customers needed to satisfy the minimum group size. Sinceboth these quantities are time-dependent, optimal bid amounts to maximizeprofits change with every impression. Consequently, traditional static biddingstrategies are far from optimal. Instead, bid values need to be optimized inreal-time to maximize expected bidder profits. This online optimization of dealprofits is made possible by the advent of ad exchanges offering real-time(spot) bidding. To this end, we propose a real-time bidding strategy forgroup-buying deals based on the online optimization of bid values. We derivethe expected bidder profit of deals as a function of the bid amounts, anddynamically vary bids to maximize profits. Further, to satisfy time constraintsof the online bidding, we present methods of minimizing computation timings.Subsequently, we derive the real time ad selection, admissibility, and realtime bidding of the traditional ads as the special cases of the proposedmethod. We evaluate the proposed bidding, selection and admission strategies ona multi-million click stream of 935 ads. The proposed real-time bidding,selection and admissibility show significant profit increases over the existingstrategies. Further the experiments illustrate the robustness of the biddingand acceptable computation timings.
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