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Cost-per-Click Pricing for Display Advertising

Author

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  • Sami Najafi-Asadolahi

    (Leavey School of Business, Santa Clara University, Santa Clara, California 95053)

  • Kristin Fridgeirsdottir

    (Management Science and Operations, London Business School, London NW1 4SA, United Kingdom)

Abstract

Display advertising is a $25 billion business with a promising upward revenue trend. In this paper, we consider an online display advertising setting in which a web publisher posts display ads on its website and charges based on the cost-per-click pricing scheme while promising to deliver a certain number of clicks to the ads posted. The publisher is faced with uncertain demand for advertising slots and uncertain traffic to its website as well as uncertain click behavior of visitors. We formulate the problem as a novel queueing system, where the slots correspond to service channels with the service rate of each server inversely related to the number of active servers. We obtain the closed-form solution for the steady-state probabilities of the number of ads in the publisher's system. We determine the publisher's optimal price to charge per click and show that it can increase in the number of advertising slots and the number of promised clicks. We show that the common heuristic used by many web publishers to convert between the cost-per-click and cost-per-impression pricing schemes using the so-called click-through-rate can be misleading because it may incur substantial revenue loss to web publishers. We provide an alternative explanation for the phenomenon observed by several publishers that the click-through-rate tends to drop when they switch from the cost-per-click to cost-per-impression pricing scheme.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:ormsom:v:16:y:2014:i:4:p:482-497
    DOI: 10.1287/msom.2014.0491
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    References listed on IDEAS

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    3. H. Mirzaei, Fouad & Ødegaard, Fredrik & Yan, Xinghao, 2015. "User reward programs in online social media," Omega, Elsevier, vol. 57(PB), pages 123-144.
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    5. Manmohan Aseri & Milind Dawande & Ganesh Janakiraman & Vijay Mookerjee, 2018. "Procurement Policies for Mobile-Promotion Platforms," Management Science, INFORMS, vol. 64(10), pages 4590-4607, October.
    6. Shen, Yuelin, 2018. "Pricing contracts and planning stochastic resources in brand display advertising," Omega, Elsevier, vol. 81(C), pages 183-194.
    7. Radha Mookerjee & Subodha Kumar & Vijay S. Mookerjee, 2017. "Optimizing Performance-Based Internet Advertisement Campaigns," Operations Research, INFORMS, vol. 65(1), pages 38-54, February.
    8. Santiago R. Balseiro & Omar Besbes & Gabriel Y. Weintraub, 2015. "Repeated Auctions with Budgets in Ad Exchanges: Approximations and Design," Management Science, INFORMS, vol. 61(4), pages 864-884, April.
    9. Radha Mookerjee & Subodha Kumar & Vijay S. Mookerjee, 2017. "Optimizing Performance-Based Internet Advertisement Campaigns," Operations Research, INFORMS, vol. 65(1), pages 38-54, February.
    10. Sameer Mehta & Milind Dawande & Ganesh Janakiraman & Vijay Mookerjee, 2020. "Sustaining a Good Impression: Mechanisms for Selling Partitioned Impressions at Ad Exchanges," Information Systems Research, INFORMS, vol. 31(1), pages 126-147, March.
    11. Hemang Subramanian & Sabyasachi Mitra & Sam Ransbotham, 2021. "Capturing Value in Platform Business Models That Rely on User-Generated Content," Organization Science, INFORMS, vol. 32(3), pages 804-823, May.
    12. Omar Besbes & Yonatan Gur & Assaf Zeevi, 2016. "Optimization in Online Content Recommendation Services: Beyond Click-Through Rates," Manufacturing & Service Operations Management, INFORMS, vol. 18(1), pages 15-33, February.
    13. Zilong Jiang & Shu Gao & Mingjiang Li, 2018. "An improved advertising CTR prediction approach based on the fuzzy deep neural network," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-24, May.
    14. Shengqi Ye & Goker Aydin & Shanshan Hu, 2015. "Sponsored Search Marketing: Dynamic Pricing and Advertising for an Online Retailer," Management Science, INFORMS, vol. 61(6), pages 1255-1274, June.
    15. Magdalena Iordache Platis & Cosmin Olteanu & Anca Luiza Hotoi, 2022. "Evolution of the Online Sales of Sustainable Products in the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    16. 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.
    17. Hana Choi & Carl F. Mela & Santiago R. Balseiro & Adam Leary, 2020. "Online Display Advertising Markets: A Literature Review and Future Directions," Information Systems Research, INFORMS, vol. 31(2), pages 556-575, June.

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