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Online advertising platforms host hundreds of thousands of A/B tests, but the platform's delivery algorithm routes each creative to the audience it predicts will engage. Every two-arm test therefore conflates the creative's effect with the…

Econometrics · Economics 2026-05-25 Pallavi Pal , Anjana Susarla

Comparison Lift is an experimentation-as-a-service (EaaS) application for testing online advertising audiences and creatives at JD.com. Unlike many other EaaS tools that focus primarily on fixed sample A/B testing, Comparison Lift deploys a…

Machine Learning · Computer Science 2020-09-18 Tong Geng , Xiliang Lin , Harikesh S. Nair , Jun Hao , Bin Xiang , Shurui Fan

Digital ads on social-media platforms play an important role in shaping access to economic opportunities. Our work proposes and implements a new third-party auditing method that can evaluate racial bias in the delivery of ads for education…

Computers and Society · Computer Science 2024-07-22 Basileal Imana , Aleksandra Korolova , John Heidemann

The code review team at Meta is continuously improving the code review process. To evaluate the new recommenders, we conduct three A/B tests which are a type of randomized controlled experimental trial. Expt 1. We developed a new…

The enormous financial success of online advertising platforms is partially due to the precise targeting features they offer. Although researchers and journalists have found many ways that advertisers can target---or exclude---particular…

Computers and Society · Computer Science 2019-09-13 Muhammad Ali , Piotr Sapiezynski , Miranda Bogen , Aleksandra Korolova , Alan Mislove , Aaron Rieke

When developing a new networking algorithm, it is established practice to run a randomized experiment, or A/B test, to evaluate its performance. In an A/B test, traffic is randomly allocated between a treatment group, which uses the new…

Networking and Internet Architecture · Computer Science 2021-10-04 Bruce Spang , Veronica Hannan , Shravya Kunamalla , Te-Yuan Huang , Nick McKeown , Ramesh Johari

A/B testing methodology is generally performed by private companies to increase user engagement and satisfaction about online features. Their usage is far from being transparent and may undermine user autonomy (e.g. polarizing individual…

Social and Information Networks · Computer Science 2024-05-03 Matteo Ottaviani , Stefan M. Herzog , Pietro Leonardo Nickl , Philipp Lorenz-Spreen

Conventional bidding strategies for online display ad auction heavily relies on observed performance indicators such as clicks or conversions. A bidding strategy naively pursuing these easily observable metrics, however, fails to optimize…

Machine Learning · Computer Science 2020-07-10 Daisuke Moriwaki , Yuta Hayakawa , Isshu Munemasa , Yuta Saito , Akira Matsui

Despite their popularity, randomized controlled trials (RCTs) are not always available for the purposes of advertising measurement. Non-experimental data is thus required. However, Facebook and other ad platforms use complex and evolving…

Econometrics · Economics 2022-10-05 Brett R. Gordon , Robert Moakler , Florian Zettelmeyer

Political campaigns are increasingly turning to digital advertising to reach voters. These platforms empower advertisers to target messages to platform users with great precision, including through inferences about those users' political…

Computers and Society · Computer Science 2019-12-18 Muhammad Ali , Piotr Sapiezynski , Aleksandra Korolova , Alan Mislove , Aaron Rieke

Online controlled experiments, such as A/B-tests, are commonly used by modern tech companies to enable continuous system improvements. Despite their paramount importance, A/B-tests are expensive: by their very definition, a percentage of…

Machine Learning · Computer Science 2024-01-09 Shubham Baweja , Neeti Pokharna , Aleksei Ustimenko , Olivier Jeunen

A/B testing is a widely-used paradigm within marketing optimization because it promises identification of causal effects and because it is implemented out of the box in most messaging delivery software platforms. Modern businesses, however,…

Machine Learning · Computer Science 2023-05-03 Schaun Wheeler

A/B testing refers to the statistical procedure of conducting an experiment to compare two treatments, A and B, applied to different testing subjects. It is widely used by technology companies such as Facebook, LinkedIn, and Netflix, to…

Methodology · Statistics 2026-05-12 Victoria Pokhiko , Qiong Zhang , Lulu Kang , D'arcy P. Mays

Mobile-phone advertising enables marketers to reach customers at a personal level and it enables the measure of costumers reaction by novel approaches, in real time, and at scale. By keeping a device anonymous, we can deliver custom adverts…

Applications · Statistics 2023-11-22 Paolo D'Alberto , Veronica Milenkiy , Fairiz Fi Azizi

Ad platforms such as Facebook, Google and LinkedIn promise value for advertisers through their targeted advertising. However, multiple studies have shown that ad delivery on such platforms can be skewed by gender or race due to hidden…

Computers and Society · Computer Science 2021-04-12 Basileal Imana , Aleksandra Korolova , John Heidemann

The problem of measuring the true incremental effectiveness of a digital advertising campaign is of increasing importance to marketers. With a large and increasing percentage of digital advertising delivered via Demand-Side-Platforms (DSPs)…

Methodology · Statistics 2017-05-04 Prasad Chalasani , Ari Buchalter , Jaynth Thiagarajan , Ezra Winston

Online advertising platforms use algorithmic systems to power the process of matching ads to users, termed ad delivery. Prior audits have demonstrated that ad delivery can be skewed by demographic attributes, such that ads are…

Computers and Society · Computer Science 2026-05-13 Isabel Corpus , Allison Koenecke

A/B testing is widexly used in the industry to optimize customer facing websites. Many companies employ experimentation specialists to facilitate and improve the process of A/B testing. Here, we present the application of A/B testing to…

Information Retrieval · Computer Science 2024-06-25 Melanie J. I. Müller

On-line experimentation (also known as A/B testing) has become an integral part of software development. To timely incorporate user feedback and continuously improve products, many software companies have adopted the culture of agile…

Applications · Statistics 2019-08-13 Yu Wang , Somit Gupta , Jiannan Lu , Ali Mahmoudzadeh , Sophia Liu

Information retrieval systems, such as online marketplaces, news feeds, and search engines, are ubiquitous in today's digital society. They facilitate information discovery by ranking retrieved items on predicted relevance, i.e. likelihood…

Econometrics · Economics 2022-05-16 Rina Friedberg , Karthik Rajkumar , Jialiang Mao , Qian Yao , YinYin Yu , Min Liu
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