research-article

Budget pacing for targeted online advertisements at LinkedIn

Authors:

Deepak Agarwal,

Siyu YouAuthors Info & Claims

KDD '14: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 1613 - 1619

https://doi.org/10.1145/2623330.2623366

Published: 24 August 2014 Publication History

Abstract

Targeted online advertising is a prime source of revenue for many Internet companies. It is a common industry practice to use a generalized second price auction mechanism to rank advertisements at every opportunity of an impression. This greedy algorithm is suboptimal for both advertisers and publishers when advertisers have a finite budget. In a greedy mechanism high performing advertisers tend to drop out of the auction marketplace fast and that adversely affects both the advertiser experience and the publisher revenue. We describe a method for improving such ad serving systems by including a budget pacing component that serves ads by being aware of global supply patterns. Such a system is beneficial for both advertisers and publishers. We demonstrate the benefits of this component using experiments we conducted on advertising at LinkedIn.

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References

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Cited By

Castiglioni MCelli AKroer CSalakhutdinov RKolter ZHeller KWeller AOliver NScarlett JBerkenkamp F(2024)Online learning under budget and ROI constraints via weak adaptivityProceedings of the 41st International Conference on Machine Learning10.5555/3692070.3692294(5792-5816)Online publication date: 21-Jul-2024
https://dl.acm.org/doi/10.5555/3692070.3692294
Karlsson N(2024)Optimization in Online Advertising via Simultaneous Adaptive Rate and Price Feedback Control2024 European Control Conference (ECC)10.23919/ECC64448.2024.10591134(499-504)Online publication date: 25-Jun-2024
https://doi.org/10.23919/ECC64448.2024.10591134
Su YXiang MChen YLi YQin TZhang HLi YLiu XBaeza-Yates RBonchi F(2024)Spending Programmed Bidding: Privacy-friendly Bid Optimization with ROI Constraint in Online AdvertisingProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671540(5731-5740)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671540
Show More Cited By

Index Terms

Budget pacing for targeted online advertisements at LinkedIn
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation theory
      1. Systems theory
2. Mathematics of computing
  1. Information theory

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cover image ACM Conferences

KDD '14: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining

August 2014

2028 pages

ISBN:9781450329569

DOI:10.1145/2623330

General Chairs:
Sofus Macskassy
Facebook
,
Claudia Perlich
Dstillery
,
Program Chairs:
Jure Leskovec
Stanford University
,
Wei Wang
UCLA
,
Rayid Ghani
University of Chicago

Copyright © 2014 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 the author(s) 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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Publication History

Published: 24 August 2014

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KDD '14: The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 24 - 27, 2014

New York, New York, USA

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KDD '14 Paper Acceptance Rate 151 of 1,036 submissions, 15%;

Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

Castiglioni MCelli AKroer CSalakhutdinov RKolter ZHeller KWeller AOliver NScarlett JBerkenkamp F(2024)Online learning under budget and ROI constraints via weak adaptivityProceedings of the 41st International Conference on Machine Learning10.5555/3692070.3692294(5792-5816)Online publication date: 21-Jul-2024
https://dl.acm.org/doi/10.5555/3692070.3692294
Karlsson N(2024)Optimization in Online Advertising via Simultaneous Adaptive Rate and Price Feedback Control2024 European Control Conference (ECC)10.23919/ECC64448.2024.10591134(499-504)Online publication date: 25-Jun-2024
https://doi.org/10.23919/ECC64448.2024.10591134
Su YXiang MChen YLi YQin TZhang HLi YLiu XBaeza-Yates RBonchi F(2024)Spending Programmed Bidding: Privacy-friendly Bid Optimization with ROI Constraint in Online AdvertisingProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671540(5731-5740)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671540
Brantley KFang ZDean SJoachims TAngélica LLattanzi SMuñoz Medina AAkoglu LGionis AVassilvitskii S(2024)Ranking with Long-Term ConstraintsProceedings of the 17th ACM International Conference on Web Search and Data Mining10.1145/3616855.3635819(47-56)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1145/3616855.3635819
Stram RAbboud RShtoff ASomekh ORaviv AKoren YChua TNgo CKumar RLauw HKa-Wei Lee R(2024)Mystique: A Budget Pacing System for Performance Optimization in Online AdvertisingCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3648342(433-442)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3648342
Chen QNguyen PGligorijevic DChua TNgo CKumar RLauw HKa-Wei Lee R(2024)Optimization-Based Budget Pacing in eBay Sponsored SearchCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3648331(328-337)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3648331
Xu WLiu SChen ZZhou YLi LWang YLu QJi YWan J(2024)ROI constrained optimal online allocation in sponsored searchScientific Reports10.1038/s41598-024-77506-314:1Online publication date: 29-Oct-2024
https://doi.org/10.1038/s41598-024-77506-3
Hajiaghayi MSpringer MAgmon NAn BRicci AYeoh W(2023)Analysis of a Learning Based Algorithm for Budget PacingProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3599051(2709-2711)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.5555/3545946.3599051
Xu JWu YWang YWang CZheng Z(2023)Online Experiments with Diminishing Marginal EffectsSSRN Electronic Journal10.2139/ssrn.4640583Online publication date: 2023
https://doi.org/10.2139/ssrn.4640583
Ou WChen BDai XZhang WLiu WTang RYu Y(2023)A Survey on Bid Optimization in Real-Time Bidding Display AdvertisingACM Transactions on Knowledge Discovery from Data10.1145/362860318:3(1-31)Online publication date: 9-Dec-2023
https://dl.acm.org/doi/10.1145/3628603
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