Abstract
Real time bidding (RTB) is becoming the key to target marketing where it could optimize advertiser expectations drastically. Not like the conventional digital advertising, in the process of RTB, the impressions of a mobile application or a website are mapped to a particular advertiser through a bidding process which triggers and held for a few milliseconds after an application is launched. To carry out the bidding process a special platform called demand side platform (DSP) provides support to advertisers to bid for available impressions on their behalf. This process has turned into a complex mission as there are many applications/websites that have come into the market. Mapping them to advertisers’ target audience, and bidding appropriately for them is not a simple human mediated process. The complexity and the dynamic nature in the RTB process make it difficult to apply forecasting strategies effectively and efficiently. In this paper we propose an autonomous and a dynamic strategy for bidding decisions such as bidding price. We applied our proposed approach on a real RTB bidding data and demonstrated that our approach can achieve higher conversion rate with the target spend for a DSP.
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Bertsekas, D.P., Bertsekas, D.P.: Dynamic programming and optimal control, vol. 1(2). Athena Scientific, Belmont (1995)
Chaitanya, N., Narahari, Y.: Optimal equilibrium bidding strategies for budget constrained bidders in sponsored search auctions. Operational Research 12(3), 317–343 (2012)
Chakraborty, T., Even-Dar, E., Guha, S., Mansour, Y., Muthukrishnan, S.: Selective call out and real time bidding. In: Saberi, A. (ed.) WINE 2010. LNCS, vol. 6484, pp. 145–157. Springer, Heidelberg (2010)
Cui, X., Lai, V.S.: Bidding strategies in online single-unit auctions: Their impact and satisfaction. Information & Management 50(6), 314–321 (2013)
Econsultancy 2013. Online Advertising Survey (2013), https://econsultancy.com/reports/online-advertising-survey/
Edelman, B., Ostrovsky, M., Schwarz, M.: Internet advertising and the generalized second price auction: Selling billions of dollars worth of keywords. National Bureau of Economic Research (2005)
Ghosh, A., McAfee, P., Papineni, K., Vassilvitskii, S.: Bidding for representative allocations for display advertising. In: Leonardi, S. (ed.) WINE 2009. LNCS, vol. 5929, pp. 208–219. Springer, Heidelberg (2009)
Hegeman, J., Yan, R., Badros, G.J.: Budget-based advertisement bidding, US Patent US20130124308 A1 (2011)
Hyndman, R.J., Koehler, A.B.: Another look at measures of forecast accuracy. International Journal of Forecasting 22(4), 679–688 (2006)
Hyndman, R.J., Khandakar, Y.: Automatic time series for forecasting: the forecast package for R (No. 6/07). Monash University, Department of Econometrics and Business Statistics (2007)
IAB 2014, Openrtb api specification version 2.2., http://www.iab.net/media/file/OpenRTBAPISpecificationVersion2_2.pdf
King, M., Mercer, A.: Problems in determining bidding strategies. Journal of the Operational Research Society, 915–923 (1985)
Li, X., Guan, D.: Programmatic Buying Bidding Strategies with Win Rate and Winning Price Estimation in Real Time Mobile Advertising. In: Tseng, V.S., Ho, T.B., Zhou, Z.-H., Chen, A.L.P., Kao, H.-Y. (eds.) PAKDD 2014, Part I. LNCS, vol. 8443, pp. 447–460. Springer, Heidelberg (2014)
Rogers, A., David, E., Payne, T.R., Jennings, N.R.: An advanced bidding agent for advertisement selection on public displays. In: Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems, p. 51. ACM (2007)
Yahalom, et al.: Bidding for impressions, U.S. Patent Application 13/282,489 (2011)
Yuan, S., Wang, J., Zhao, X.: Real-time bidding for online advertising: measurement and analysis. In: Proceedings of the Seventh International Workshop on Data Mining for Online Advertising, p. 3. ACM (2013)
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Adikari, S., Dutta, K. (2015). Real Time Bidding in Online Digital Advertisement. In: Donnellan, B., Helfert, M., Kenneally, J., VanderMeer, D., Rothenberger, M., Winter, R. (eds) New Horizons in Design Science: Broadening the Research Agenda. DESRIST 2015. Lecture Notes in Computer Science(), vol 9073. Springer, Cham. https://doi.org/10.1007/978-3-319-18714-3_2
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DOI: https://doi.org/10.1007/978-3-319-18714-3_2
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