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A Unified Framework for the Scheduling of Guaranteed Targeted Display Advertising Under Reach and Frequency Requirements

Author

Listed:
  • Ali Hojjat

    (Peter T. Paul College of Business and Economics, University of New Hampshire, Durham, New Hampshire 03824)

  • John Turner

    (The Paul Merage School of Business, University of California Irvine, Irvine, California 92697)

  • Suleyman Cetintas

    (Yahoo Research, Sunnyvale, California 94089)

  • Jian Yang

    (Yahoo Research, Sunnyvale, California 94089)

Abstract

Motivated by recent trends in online advertising and advancements made by online publishers, we consider a new form of contract that allows advertisers to specify the number of unique individuals that should see their ad ( reach ) and the minimum number of times each individual should be exposed ( frequency ). We develop an optimization framework that aims for minimal under-delivery and proper spread of each campaign over its targeted demographics. As well, we introduce a pattern -based delivery mechanism that allows us to integrate a variety of interesting features into a website’s ad allocation optimization problem that have not been possible before. For example, our approach allows publishers to implement any desired pacing of ads over time at the user level or control the number of competing brands seen by each individual. We develop a two-phase algorithm that employs column generation in a hierarchical scheme with three parallelizable components. Numerical tests with real industry data show that our algorithm produces high-quality solutions and has promising run-time and scalability. Several extensions of the model are presented, e.g., to account for multiple ad positions on the webpage or randomness in the website visitors’ arrival process.

Suggested Citation

  • Ali Hojjat & John Turner & Suleyman Cetintas & Jian Yang, 2017. "A Unified Framework for the Scheduling of Guaranteed Targeted Display Advertising Under Reach and Frequency Requirements," Operations Research, INFORMS, vol. 65(2), pages 289-313, April.
    • Handle: RePEc:inm:oropre:v:65:y:2017:i:2:p:289-313
    DOI: 10.1287/opre.2016.1567
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    References listed on IDEAS

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    1. Sami Najafi-Asadolahi & Kristin Fridgeirsdottir, 2014. "Cost-per-Click Pricing for Display Advertising," Manufacturing & Service Operations Management, INFORMS, vol. 16(4), pages 482-497, October.
    2. Radha Mookerjee & Subodha Kumar & Vijay S. Mookerjee, 2012. "To Show or Not Show: Using User Profiling to Manage Internet Advertisement Campaigns at Chitika," Interfaces, INFORMS, vol. 42(5), pages 449-464, October.
    3. Santiago R. Balseiro & Jon Feldman & Vahab Mirrokni & S. Muthukrishnan, 2014. "Yield Optimization of Display Advertising with Ad Exchange," Management Science, INFORMS, vol. 60(12), pages 2886-2907, December.
    4. Gustav Feichtinger & Richard F. Hartl & Suresh P. Sethi, 1994. "Dynamic Optimal Control Models in Advertising: Recent Developments," Management Science, INFORMS, vol. 40(2), pages 195-226, February.
    5. Vahideh H. Manshadi & Shayan Oveis Gharan & Amin Saberi, 2012. "Online Stochastic Matching: Online Actions Based on Offline Statistics," Mathematics of Operations Research, INFORMS, vol. 37(4), pages 559-573, November.
    6. P. C. Gilmore & R. E. Gomory, 1961. "A Linear Programming Approach to the Cutting-Stock Problem," Operations Research, INFORMS, vol. 9(6), pages 849-859, December.
    7. Marco E. Lübbecke & Jacques Desrosiers, 2005. "Selected Topics in Column Generation," Operations Research, INFORMS, vol. 53(6), pages 1007-1023, December.
    8. Shipra Agrawal & Zizhuo Wang & Yinyu Ye, 2014. "A Dynamic Near-Optimal Algorithm for Online Linear Programming," Operations Research, INFORMS, vol. 62(4), pages 876-890, August.
    9. John Turner, 2012. "The Planning of Guaranteed Targeted Display Advertising," Operations Research, INFORMS, vol. 60(1), pages 18-33, February.
    10. David Maxwell Chickering & David Heckerman, 2003. "Targeted Advertising on the Web with Inventory Management," Interfaces, INFORMS, vol. 33(5), pages 71-77, October.
    11. Dylan Jones & Mehrdad Tamiz, 2010. "Practical Goal Programming," International Series in Operations Research and Management Science, Springer, edition 1, number 978-1-4419-5771-9, September.
    12. Campbell, Margaret C & Keller, Kevin Lane, 2003. "Brand Familiarity and Advertising Repetition Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 292-304, September.
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    4. Huaxiao Shen & Yanzhi Li & Jingjing Guan & Geoffrey K.F. Tso, 2021. "A Planning Approach to Revenue Management for Non‐Guaranteed Targeted Display Advertising," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1583-1602, June.
    5. Zikun Ye & Dennis J. Zhang & Heng Zhang & Renyu Zhang & Xin Chen & Zhiwei Xu, 2023. "Cold Start to Improve Market Thickness on Online Advertising Platforms: Data-Driven Algorithms and Field Experiments," Management Science, INFORMS, vol. 69(7), pages 3838-3860, July.
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    7. Raghav Singal & Omar Besbes & Antoine Desir & Vineet Goyal & Garud Iyengar, 2022. "Shapley Meets Uniform: An Axiomatic Framework for Attribution in Online Advertising," Management Science, INFORMS, vol. 68(10), pages 7457-7479, October.

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