IDEAS home Printed from https://ideas.repec.org/a/pal/jmarka/v6y2018i2d10.1057_s41270-018-0031-0.html
   My bibliography  Save this article

User-level incremental conversion ranking without A/B testing

Author

Listed:
  • Zhuli Xie

    (Oath Inc.)

  • Yong Liu

    (Oath Inc.)

Abstract

The traditional approach to build incremental conversion prediction model has to rely on A/B test results. However, under certain intense business environment, A/B testing can be limited by technical support, platform, or budget, and become not practically available. In this paper, we propose an algorithm to rank users by incremental conversions resulted from advertising effects, which is based on user’s conversion history and the output from a conversion prediction model. By appropriately defining who an active user is, this algorithm is proven to work well with real data. In case where an A/B test is not available and incremental conversion-based user targeting is desired, this algorithm offers a practical solution.

Suggested Citation

  • Zhuli Xie & Yong Liu, 2018. "User-level incremental conversion ranking without A/B testing," Journal of Marketing Analytics, Palgrave Macmillan, vol. 6(2), pages 62-68, June.
    • Handle: RePEc:pal:jmarka:v:6:y:2018:i:2:d:10.1057_s41270-018-0031-0
    DOI: 10.1057/s41270-018-0031-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41270-018-0031-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1057/s41270-018-0031-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. David S. Evans, 2009. "The Online Advertising Industry: Economics, Evolution, and Privacy," Journal of Economic Perspectives, American Economic Association, vol. 23(3), pages 37-60, Summer.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bodo Herzog, 2018. "Valuation of Digital Platforms: Experimental Evidence for Google and Facebook," IJFS, MDPI, vol. 6(4), pages 1-13, October.
    2. A. Daly & A. Scardamaglia, 2017. "Profiling the Australian Google Consumer: Implications of Search Engine Practices for Consumer Law and Policy," Journal of Consumer Policy, Springer, vol. 40(3), pages 299-320, September.
    3. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    4. Abdullah Yahia Moqbile Ahmed, 2017. "The Impact of Exposure to Advertisement Online on Purchase Decision Empirical Study of Saudi Customers in Western Region," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 7(7), pages 366-386, July.
    5. Alvin J. Silk & Marta M. Stiglin, 2016. "Build It, Buy It, or Both? Rethinking the Sourcing of Advertising Services," International Journal of Marketing Studies, Canadian Center of Science and Education, vol. 8(1), pages 1-13, February.
    6. Liu Xingyi, 2016. "Fear of Discrimination: Net Neutrality and Product Differentiation on the Internet," Review of Network Economics, De Gruyter, vol. 15(4), pages 211-247, December.
    7. Bayer, Emanuel & Srinivasan, Shuba & Riedl, Edward J. & Skiera, Bernd, 2020. "The impact of online display advertising and paid search advertising relative to offline advertising on firm performance and firm value," International Journal of Research in Marketing, Elsevier, vol. 37(4), pages 789-804.
    8. Wei Zhou & Zidong Wang, 2020. "Competing for Search Traffic in Query Markets: Entry Strategy, Platform Design, and Entrepreneurship," Working Papers 20-12, NET Institute.
    9. Avi Goldfarb, 2014. "What is Different About Online Advertising?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 44(2), pages 115-129, March.
    10. Rajeev Goel, 2011. "Persistence of cigarette advertising across media and smoking rates," Applied Economics Letters, Taylor & Francis Journals, vol. 18(7), pages 611-619.
    11. Hannah Bensussan, 2023. "Understanding the paradox of control and freedom of consumption under digital capitalism with Stafford Beer's cybernetic theory," Working Papers hal-04050331, HAL.
    12. Andreas Hefti & Shuo Liu, 2020. "Targeted information and limited attention," RAND Journal of Economics, RAND Corporation, vol. 51(2), pages 402-420, June.
    13. Mpinganjira, Mercy & Maduku, Daniel K., 2019. "Ethics of mobile behavioral advertising: Antecedents and outcomes of perceived ethical value of advertised brands," Journal of Business Research, Elsevier, vol. 95(C), pages 464-478.
    14. Hartmut Egger & Josef Falkinger, 2016. "Limited Consumer Attention in International Trade," Review of International Economics, Wiley Blackwell, vol. 24(5), pages 1096-1128, November.
    15. Nadine Lindstädt & Oliver Budzinski, 2011. "Newspaper vs. Online Advertising – Is There a Niche for Newspapers in Modern Advertising Markets?," Working Papers 113/11, University of Southern Denmark, Department of Sociology, Environmental and Business Economics.
    16. Amedeo Piolatto, 2015. "Online booking and information: competition and welfare consequences of review aggregators," Working Papers 2015/11, Institut d'Economia de Barcelona (IEB).
    17. Salome Baslandze & Jeremy Greenwood & Ricardo Marto & Sara Moreira, 2023. "The Expansion of Varieties in the New Age of Advertising," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 50, pages 171-210, October.
    18. He Xi & Lopez Rigoberto & Liu Yizao, 2017. "Are Online and Offline Advertising Substitutes or Complements? Evidence from U.S. Food Industries," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 15(2), pages 1-10, December.
    19. Jonathan Timmis, 2012. "The Internet and International Trade in Goods," Discussion Papers 12/08, University of Nottingham, GEP.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jmarka:v:6:y:2018:i:2:d:10.1057_s41270-018-0031-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.