Business & Information Systems Engineering

, Volume 6, Issue 5, pp 305–308 | Cite as

Real-Time Advertising

  • Martin Stange
  • Burkhardt FunkEmail author

Data-Driven Online Advertising

Over the last two decades, online advertising has become one of the most important elements of corporate communications. Whereas static banner ads dominated initially, search advertising (Varian 2007) now encompasses the largest part of global online advertising spending. In recent years, a new form of online advertising, real-time advertising1 (RTA), has been increasingly used. RTA is based on auctions in which individual advertising spaces are sold within a few milliseconds after calling a website. Advertisers or their media agencies participate in these auctions. RTA was first established in the U.S. and is now represented in the German market, with a market share of approximately 10 % (BVDW 2013). RTA will progressively replace the traditional forms of purchasing online advertising space, which nowadays is being sold in large quotas and at predetermined prices that are mediated by marketers and media agencies. Thus, from the perspective of...


Business Model User Behavior Online Advertising Automate Decision Advertising Spending 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Balseiro S, Feldman J, Mirrokni V, Muthukrishnan S (2011) Yield optimization of display advertising with ad exchange. In: Proc 12th ACM conf electron commer Google Scholar
  2. BVDW (2013) Real Time Advertising Kompass 2013/2014. Düsseldorf Google Scholar
  3. Carrascal J, Riederer C (2013) Your browsing behavior for a big mac: economics of personal information online. In: Proc 22nd int conf world wide web, pp 189–200 Google Scholar
  4. Ghosh A, McAfee P, Papineni K, Vassilvitskii S (2009) Bidding for representative allocations for display advertising. Lect Notes Comput Sci 5929:208–219 CrossRefGoogle Scholar
  5. Goldfarb A, Tucker C (2011) Privacy regulation and online advertising. Manag Sci 57:57–71 CrossRefGoogle Scholar
  6. Google (2014) Real time bidding protokol. Accessed 2014-06-19
  7. Nottorf F (2014) Modeling the clickstream across multiple online advertising channels using a binary logit with Bayesian mixture of normals. Electron Commer Res Appl 13:45–55 CrossRefGoogle Scholar
  8. Nottorf F, Funk B (2013) The economic value of clickstream data from an advertiser’s perspective. In: 22nd Eur conf inf syst Google Scholar
  9. Perlich C, Dalessandro B, Hook R (2012) Bid optimizing and inventory scoring in targeted online advertising. In: Proc 18th ACM SIGKDD int conf knowl discov data min, pp 804–812 CrossRefGoogle Scholar
  10. Probst F, Buhl HU (2012) Supplier portfolio management for IT services considering diversification effects. Bus Inf Syst Eng 4(2):71–83 CrossRefGoogle Scholar
  11. Varian HR (2007) Position auctions. Int J Ind Organ 25:1163–1178 CrossRefGoogle Scholar
  12. Veit D, Clemons E, Benlian A, Buxmann P, Hess T, Kundisch D, Leimeister JM, Loos P, Spann M (2014) Business models. Bus Inf Syst Eng 6(1):45–53 CrossRefGoogle Scholar

Copyright information

© Springer Fachmedien Wiesbaden 2014

Authors and Affiliations

  1. 1.Fakultät WirtschaftswissenschaftenLeuphana University LüneburgLüneburgGermany

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