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Blending Advertising with Organic Content in E-Commerce: A Virtual Bids Optimization Approach

Author

Listed:
  • Carrion, Carlos

    (JD.com)

  • Wang, Zenan

    (JD.com)

  • Nair, Harikesh

    (Stanford University)

  • Luo, Xianghong

    (JD.com)

  • Lei, Yulin

    (JD.com)

  • Lin, Xiliang

    (JD.com)

  • Chen, Wenlong

    (JD.com)

  • Hu, Qiyu

    (JD.com)

  • Peng, Changping

    (JD.com)

  • Bao, Yongjun

    (JD.com)

  • Yan, Weipeng

    (JD.com)

Abstract

In e-commerce platforms, sponsored and non-sponsored content are jointly displayed to users and both may interactively influence their engagement behavior. The former content helps advertisers achieve their marketing goals and provides a stream of ad revenue to the platform. The latter content contributes to users’ engagement with the platform, which is key to its long-term health. A burning issue for e-commerce platform design is how to blend advertising with content in a way that respects these interactions and balances these multiple business objectives. This paper describes a system developed for this purpose in the context of blending personalized sponsored content with non-sponsored content on the product detail pages of JD.com, an e-commerce company. This system has three key features: (1) Optimization of multiple competing business objectives through a new virtual bids approach and the expressiveness of the latent, implicit valuation of the platform for the multiple objectives via these virtual bids. (2) Modeling of users’ click behavior as a function of their characteristics, the individual characteristics of each sponsored content and the influence exerted by other sponsored and non-sponsored content displayed alongside through a deep learning approach; (3) Consideration of externalities in the allocation of ads, thereby making it directly compatible with a Vickrey-Clarke-Groves (VCG) auction scheme for the computation of payments in the presence of these externalities. The system is currently deployed and serving all traffic through JD.coms mobile application. Experiments demonstrating the performance and advantages of the system are presented.

Suggested Citation

  • Carrion, Carlos & Wang, Zenan & Nair, Harikesh & Luo, Xianghong & Lei, Yulin & Lin, Xiliang & Chen, Wenlong & Hu, Qiyu & Peng, Changping & Bao, Yongjun & Yan, Weipeng, 2021. "Blending Advertising with Organic Content in E-Commerce: A Virtual Bids Optimization Approach," Research Papers 3967, Stanford University, Graduate School of Business.
    • Handle: RePEc:ecl:stabus:3967
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    References listed on IDEAS

    as
    1. Stephen A. Rhoades, 1993. "The Herfindahl-Hirschman index," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Mar, pages 188-189.
    2. Hal R. Varian & Christopher Harris, 2014. "The VCG Auction in Theory and Practice," American Economic Review, American Economic Association, vol. 104(5), pages 442-445, May.
    3. Marshall L. Fisher, 1981. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 27(1), pages 1-18, January.
    4. repec:cup:cbooks:9781316779309 is not listed on IDEAS
    5. Roughgarden,Tim, 2016. "Twenty Lectures on Algorithmic Game Theory," Cambridge Books, Cambridge University Press, number 9781316624791, January.
    6. Roughgarden,Tim, 2016. "Twenty Lectures on Algorithmic Game Theory," Cambridge Books, Cambridge University Press, number 9781107172661, January.
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    Cited by:

    1. George Z. Gui, 2024. "Combining Observational and Experimental Data to Improve Efficiency Using Imperfect Instruments," Marketing Science, INFORMS, vol. 43(2), pages 378-391, March.

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