research-article

To Match or Not to Match: Economics of Cookie Matching in Online Advertising

Authors:

Mohammad Mahdian,

R. Preston McAfee,

Sergei VassilvitskiiAuthors Info & Claims

ACM Transactions on Economics and Computation (TEAC), Volume 3, Issue 2

Article No.: 12, Pages 1 - 18

https://doi.org/10.1145/2745801

Published: 20 April 2015 Publication History

Abstract

Modern online advertising increasingly relies on the ability to follow the same user across the Internet using technology called cookie matching to increase efficiency in ad allocation. Web publishers today use this technology to share information about the websites a user has visited, making it possible to target advertisements to users based on their prior history. This begs the question: do publishers (who are competitors for advertising money) always have the incentive to share online information? Intuitive arguments as well as anecdotal evidence suggest that sometimes a premium publisher might suffer information sharing through an effect called information leakage: by sharing user information with the advertiser, the advertiser will be able to target the same user elsewhere on cheaper publishers, leading to a dilution of the value of the supply on the premium publishers.

The goal of this article is to explore this aspect of online information sharing. We show that, when advertisers are homogeneous in the sense that their relative valuations of users are consistent, publishers always agree about the benefits of cookie matching in equilibrium: either all publishers’ revenues benefit, or all suffer, from cookie matching. We also show using a simple model that, when advertisers are not homogeneous, the information leakage indeed can occur, with cookie matching helping one publisher’s revenues while harming the other.

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Cited By

Liao GChen XHuang J(2022)Privacy-Aware Online Social Networking With Targeted AdvertisementIEEE/ACM Transactions on Networking10.1109/TNET.2021.313751330:3(1312-1327)Online publication date: Jun-2022
https://doi.org/10.1109/TNET.2021.3137513
Di Tizio GMassacci F(2021)A Calculus of Tracking: Theory and PracticeProceedings on Privacy Enhancing Technologies10.2478/popets-2021-00272021:2(259-281)Online publication date: 29-Jan-2021
https://doi.org/10.2478/popets-2021-0027
Sanchez-Rola IDell'Amico MBalzarotti DVervier PBilge L(2021)Journey to the Center of the Cookie Ecosystem: Unraveling Actors' Roles and Relationships2021 IEEE Symposium on Security and Privacy (SP)10.1109/SP40001.2021.9796062(1990-2004)Online publication date: May-2021
https://doi.org/10.1109/SP40001.2021.9796062
Show More Cited By

Index Terms

To Match or Not to Match: Economics of Cookie Matching in Online Advertising
1. Applied computing
  1. Law, social and behavioral sciences

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Reviews

Reviewer: Salvatore F. Pileggi

Cookies are extensively adopted in the current web scenario. A cookie is a small file placed on a user's computer that permits a website to record information about a previous visit. From a strictly technical perspective, they contribute to a better user experience, for example, allowing a user to stay logged in on a website and a website to remember user preferences. In practice, cookies have a significant impact on commercial markets as they can be (and are) used to target advertising. Recent trends clearly show websites, even competitors, sharing cookie information, generating the well-known concerns about user privacy. This paper discuss information leakage in a commercial context where cookie matching could have, under the hypothesis of ideal conditions (in equilibrium), a fair impact on the market or could lead, in inhomogeneous conditions, to unbalanced perturbations. Indeed, in the latter case, information leakage determines imbalances that could help one (or few ones) and harm many ones (against the balanced model that produces the same benefit or damage for everyone). I definitely enjoyed reading this paper for its clear premise, the strong approach, the rich model adopted for the analysis of the dynamics of interest across multiple scenarios, and the further directions previewed by the authors, including the analysis of other economic phenomena (such as market fragmentation). Online Computing Reviews Service

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Information & Contributors

Information

Published In

cover image ACM Transactions on Economics and Computation

ACM Transactions on Economics and Computation Volume 3, Issue 2

Special Issue on EC'12, Part 2

April 2015

171 pages

ISSN:2167-8375

EISSN:2167-8383

DOI:10.1145/2764902

Editors:
Vincent Conitzer
Duke University
,
Preston McAfee
Google

Issue’s Table of Contents

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 April 2015

Accepted: 01 May 2014

Revised: 01 January 2014

Received: 01 May 2013

Published in TEAC Volume 3, Issue 2

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Cited By

Liao GChen XHuang J(2022)Privacy-Aware Online Social Networking With Targeted AdvertisementIEEE/ACM Transactions on Networking10.1109/TNET.2021.313751330:3(1312-1327)Online publication date: Jun-2022
https://doi.org/10.1109/TNET.2021.3137513
Di Tizio GMassacci F(2021)A Calculus of Tracking: Theory and PracticeProceedings on Privacy Enhancing Technologies10.2478/popets-2021-00272021:2(259-281)Online publication date: 29-Jan-2021
https://doi.org/10.2478/popets-2021-0027
Sanchez-Rola IDell'Amico MBalzarotti DVervier PBilge L(2021)Journey to the Center of the Cookie Ecosystem: Unraveling Actors' Roles and Relationships2021 IEEE Symposium on Security and Privacy (SP)10.1109/SP40001.2021.9796062(1990-2004)Online publication date: May-2021
https://doi.org/10.1109/SP40001.2021.9796062
Pooranian ZConti MHaddadi HTafazolli R(2021)Online Advertising Security: Issues, Taxonomy, and Future DirectionsIEEE Communications Surveys & Tutorials10.1109/COMST.2021.311827123:4(2494-2524)Online publication date: Dec-2022
https://doi.org/10.1109/COMST.2021.3118271
Cook JNithyanand RShafiq Z(2020)Inferring Tracker-Advertiser Relationships in the Online Advertising Ecosystem using Header BiddingProceedings on Privacy Enhancing Technologies10.2478/popets-2020-00052020:1(65-82)Online publication date: 7-Jan-2020
https://doi.org/10.2478/popets-2020-0005
Choi HMela CBalseiro SLeary A(2020)Online Display Advertising MarketsInformation Systems Research10.1287/isre.2019.090231:2(556-575)Online publication date: 1-Jun-2020
https://dl.acm.org/doi/10.1287/isre.2019.0902
Yu HWei EBerry R(2019)Analyzing Location-Based Advertising for Vehicle Service Providers Using Effective ResistancesACM SIGMETRICS Performance Evaluation Review10.1145/3376930.337695547:1(37-38)Online publication date: 17-Dec-2019
https://dl.acm.org/doi/10.1145/3376930.3376955
Yu HWei EBerry R(2019)Analyzing Location-Based Advertising for Vehicle Service Providers Using Effective ResistancesProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/3322205.33110773:1(1-35)Online publication date: 26-Mar-2019
https://dl.acm.org/doi/10.1145/3322205.3311077
Yu HWei EBerry RNahum EBonald TDuffield N(2019)Analyzing Location-Based Advertising for Vehicle Service Providers Using Effective ResistancesAbstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems10.1145/3309697.3331484(37-38)Online publication date: 20-Jun-2019
https://dl.acm.org/doi/10.1145/3309697.3331484
Papadopoulos PKourtellis NMarkatos E(2019)Cookie Synchronization: Everything You Always Wanted to Know But Were Afraid to AskThe World Wide Web Conference10.1145/3308558.3313542(1432-1442)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308558.3313542
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