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What factors affect targeting and bids in online advertising?: a field measurement study

Authors:

Tadayoshi Kohno,

Franziska RoesnerAuthors Info & Claims

IMC '22: Proceedings of the 22nd ACM Internet Measurement Conference

Pages 210 - 229

https://doi.org/10.1145/3517745.3561460

Published: 25 October 2022 Publication History

Abstract

Targeted online advertising is a well-known but extremely opaque phenomenon. Though the targeting capabilities of the ad tech ecosystem are public knowledge, from an outside perspective, it is difficult to measure and quantify ad targeting at scale. To shed light on the extent of targeted advertising on the web today, we conducted a controlled field measurement study of the ads shown to a representative sample of 286 participants in the U.S. Using a browser extension, we collected data on ads seen by users on 10 popular websites, including the topic of the ad, the value of the bid placed by the advertiser (via header bidding), and participants' perceptions of targeting. We analyzed how ads were targeted across individuals, websites, and demographic groups, how those factors affected the amount advertisers bid, and how those results correlated with participants' perceptions of targeting. Among our findings, we observed that the primary factors that affected targeting and bid values were the website the ad appeared on and individual user profiles. Surprisingly, we found few differences in how advertisers target and bid across demographic groups. We also found that high outliers in bid values (10x higher than baseline) may be indicative of retargeting. Our measurements provide a rare in situ view of targeting and bidding across a diversity of users.

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Index Terms

What factors affect targeting and bids in online advertising?: a field measurement study
1. Information systems
  1. World Wide Web
    1. Online advertising

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Published In

cover image ACM Conferences

IMC '22: Proceedings of the 22nd ACM Internet Measurement Conference

October 2022

796 pages

ISBN:9781450392594

DOI:10.1145/3517745

General Chairs:
Chadi Barakat
Inria, Université Côte d'Azur
,
Cristel Pelsser
University of Strasbourg
,
Program Chairs:
Theophilus A. Benson
Brown University
,
David Choffnes
Northeastern University

Copyright © 2022 Owner/Author.

This work is licensed under a Creative Commons Attribution-NonCommercial International 4.0 License.

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USENIX Assoc: USENIX Assoc

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 October 2022

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National Science Foundation

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IMC '22

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IMC '22: ACM Internet Measurement Conference

October 25 - 27, 2022

Nice, France

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Overall Acceptance Rate 277 of 1,083 submissions, 26%

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Cited By

Zhu TShou CHuang ZChen GZhang XMeng YHao SZhu HLuo BLiao XXu JKirda ELie D(2024)Unveiling Collusion-Based Ad Attribution Laundering Fraud: Detection, Analysis, and Security ImplicationsProceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security10.1145/3658644.3670314(2963-2977)Online publication date: 2-Dec-2024
https://dl.acm.org/doi/10.1145/3658644.3670314
Yeung CKohno TRoesner FVallina-Rodríguez NSuarez-Tángil GLevin DPelsser C(2024)Analyzing the (In)Accessibility of Online AdvertisementsProceedings of the 2024 ACM on Internet Measurement Conference10.1145/3646547.3688427(92-106)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3646547.3688427
Chen CLi WSong WYe YYao YLi T(2024)An Empathy-Based Sandbox Approach to Bridge the Privacy Gap among Attitudes, Goals, Knowledge, and BehaviorsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642363(1-28)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642363
Schnadower Mustri EAdjerid IAcquisti A(2023)Behavioral Advertising and Consumer Welfare: An Empirical InvestigationSSRN Electronic Journal10.2139/ssrn.4398428Online publication date: 2023
https://doi.org/10.2139/ssrn.4398428
Lam MPandit AKalicki CGupta RSahoo PMetaxa D(2023)Sociotechnical Audits: Broadening the Algorithm Auditing Lens to Investigate Targeted AdvertisingProceedings of the ACM on Human-Computer Interaction10.1145/36102097:CSCW2(1-37)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3610209

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