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Lookalike Targeting on Others' Journeys: Brand Versus Performance Marketing

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Abstract

Lookalike Targeting is a widely used model-based ad targeting approach that uses a seed database of individuals to identify matching "lookalikes" for targeted customer acquisition. An advertiser has to make two key choices: (1) who to seed on and (2) seed-match rank range. First, we assess if and how seeding by others' journey stages impact clickthrough (upstream behavior desirable for brand marketing) and donation (downstream behavior desirable in performance marketing). Overall, we find that lookalike targeting using other's journeys can be effective-third parties can indeed identify factors unobserved to the advertiser merely from others' journey stage to improve targeting. Further, while it is sufficient to seed on upstream journey stages for brand marketing, seeding on more downstream stages improves performance marketing outcomes. Second, we assess the effectiveness of expanding the target audience with lower match ranks between seed and lookalikes. The drop in effectiveness with lower match rank range is much greater for performance marketing (donation) than for brand marketing (click-through). However, performance marketers can alleviate the reduction in ad effectiveness for low match ranks by making targeting more salient; but increasing salience has little impact for high match rank. Overall, by increasing salience, performance marketers can make acquisition cost comparable for high and low match ranks.

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  • K. Sudhir & Seung Yoon Lee & Subroto Roy, 2021. "Lookalike Targeting on Others' Journeys: Brand Versus Performance Marketing," Cowles Foundation Discussion Papers 2302, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:2302
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    1. Bharat Anand & Ron Shachar, 2009. "Targeted advertising as a signal," Quantitative Marketing and Economics (QME), Springer, vol. 7(3), pages 237-266, September.
    2. Nico Neumann & Catherine E. Tucker & Timothy Whitfield, 2019. "Frontiers: How Effective Is Third-Party Consumer Profiling? Evidence from Field Studies," Marketing Science, INFORMS, vol. 38(6), pages 918-926, November.
    3. Nejad, Mohammad G. & Amini, Mehdi & Babakus, Emin, 2015. "Success Factors in Product Seeding: The Role of Homophily," Journal of Retailing, Elsevier, vol. 91(1), pages 68-88.
    4. Avi Goldfarb & Catherine Tucker, 2011. "Online Display Advertising: Targeting and Obtrusiveness," Marketing Science, INFORMS, vol. 30(3), pages 389-404, 05-06.
    5. Avi Goldfarb & Catherine Tucker, 2011. "Rejoinder--Implications of "Online Display Advertising: Targeting and Obtrusiveness"," Marketing Science, INFORMS, vol. 30(3), pages 413-415, 05-06.
    6. Chenxi Li & Xueming Luo & Cheng Zhang, 2017. "Sunny, Rainy, and Cloudy with a Chance of Mobile Promotion Effectiveness," Marketing Science, INFORMS, vol. 36(5), pages 762-779, September.
    7. Christopher A. Summers & Robert W. Smith & Rebecca Walker Reczek, 2016. "An Audience of One: Behaviorally Targeted Ads as Implied Social Labels," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 43(1), pages 156-178.
    8. Stephan Seiler & Song Yao, 2017. "The impact of advertising along the conversion funnel," Quantitative Marketing and Economics (QME), Springer, vol. 15(3), pages 241-278, September.
    9. Hinz, Oliver & Skiera, Bernd & Barrot, Christian & Becker, Jan, 2011. "Seeding Strategies for Viral Marketing: An Empirical Comparison," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56543, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    10. Tiffany White & Debra Zahay & Helge Thorbjørnsen & Sharon Shavitt, 2008. "Getting too personal: Reactance to highly personalized email solicitations," Marketing Letters, Springer, vol. 19(1), pages 39-50, March.
    11. Aral, Sinan & Muchnik, Lev & Sundararajan, Arun, 2013. "Engineering social contagions: Optimal network seeding in the presence of homophily," Network Science, Cambridge University Press, vol. 1(2), pages 125-153, August.
    12. Peter E. Rossi & Robert E. McCulloch & Greg M. Allenby, 1996. "The Value of Purchase History Data in Target Marketing," Marketing Science, INFORMS, vol. 15(4), pages 321-340.
    13. Zhenling Jiang & Tat Chan & Hai Che & Youwei Wang, 2021. "Consumer Search and Purchase: An Empirical Investigation of Retargeting Based on Consumer Online Behaviors," Marketing Science, INFORMS, vol. 40(2), pages 219-240, March.
    14. Michael Trusov & Liye Ma & Zainab Jamal, 2016. "Crumbs of the Cookie: User Profiling in Customer-Base Analysis and Behavioral Targeting," Marketing Science, INFORMS, vol. 35(3), pages 405-426, May.
    15. Jenny Doorn & Janny Hoekstra, 2013. "Customization of online advertising: The role of intrusiveness," Marketing Letters, Springer, vol. 24(4), pages 339-351, December.
    16. Vineet Kumar & K. Sudhir, 2019. "Can Friends Seed More Buzz and Adoption"," Cowles Foundation Discussion Papers 2178, Cowles Foundation for Research in Economics, Yale University.
    17. Anindya Ghose & Beibei Li & Siyuan Liu, 2019. "Mobile Targeting Using Customer Trajectory Patterns," Management Science, INFORMS, vol. 65(11), pages 5027-5049, November.
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    More about this item

    Keywords

    Digital advertising; Targeting; Algorithmic targeting; Lookalike targeting; Nonprofit marketing;
    All these keywords.

    JEL classification:

    • L31 - Industrial Organization - - Nonprofit Organizations and Public Enterprise - - - Nonprofit Institutions; NGOs; Social Entrepreneurship
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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