Untangling Header Bidding Lore: Some Myths, Some Truths, and Some Hope

Waqar Aqeel, Debopam Bhattacherjee, Balakrishnan Chandrasekaran, P. Brighten Godfrey, Gregory Laughlin, Bruce Maggs, Ankit Singla

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Header bidding (HB) is a relatively new online advertising technology that allows a content publisher to conduct a client-side (i.e., from within the end-user’s browser), real-time auction for selling ad slots on a web page. We developed a new browser extension for Chrome and Firefox to observe this in-browser auction process from the user’s perspective. We use real end-user measurements from 393,400 HB auctions to (a) quantify the ad revenue from HB auctions, (b) estimate latency overheads when integrating with ad exchanges and discuss their implications for ad revenue, and (c) break down the time spent in soliciting bids from ad exchanges into various factors and highlight areas for improvement. For the users in our study, we find that HB increases ad revenue for web sites by 28% compared to that in real-time bidding as reported in a prior work. We also find that the latency overheads in HB can be easily reduced or eliminated and outline a few solutions, and pitch the HB platform as an opportunity for privacy-preserving advertising.

Original languageEnglish (US)
Title of host publicationPassive and Active Measurement - 21st International Conference, PAM 2020, Proceedings
EditorsAnna Sperotto, Alberto Dainotti, Burkhard Stiller
Number of pages18
ISBN (Print)9783030440800
StatePublished - 2020
Event21st International Conference on Passive and Active Measurement, PAM 2020 - Eugene, United States
Duration: Mar 30 2020Mar 31 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12048 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference21st International Conference on Passive and Active Measurement, PAM 2020
CountryUnited States

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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