-
We introduce OpportunityFinder, a code-less framework for performing a variety of causal inference studies with panel data for non-expert users. In its current state, OpportunityFinder only requires users to provide raw observational data and a configuration file. A pipeline is then triggered that inspects/processes data, chooses the suitable algorithm(s) to execute the causal study. It returns the causal
-
Applied Marketing Analytics (AMA)2023Brands usually invest in a portfolio of digital ad products for brand consideration and conversion, and their performance is commonly evaluated with ad - attributed metrics. However, these metrics limit the measurement of advertising effectiveness within a short time window, typically of two weeks. Therefore, they could underestimate the total effect if some ad products' efficacy lasts beyond the measurement
-
KDD 2023 Workshop on Multi-Armed Bandits and Reinforcement Learning (MARBLE), ICML 2023 Workshop on The Many Facets of Preference-based Learning2023Motivated by bid recommendation in online ad auctions, this paper considers a general class of multi-level and multi-agent games, with two major characteristics: one is a large number of anonymous agents, and the other is the intricate interplay between competition and cooperation. To model such complex systems, we propose a novel and tractable bi-objective optimization formulation with mean-field approximation
-
This paper proposes a learning model of online ad auctions that allows for the following four key realistic characteristics of contemporary online auctions: (1) ad slots can have different values and click-through rates depending on users’ search queries, (2) the number and identity of competing advertisers are unobserved and change with each auction, (3) advertisers only receive partial, aggregated feedback
-
Companies offering web services routinely run randomized online experiments to estimate the “causal impact” associated with the adoption of new features and policies on key performance metrics of interest. These experiments are used to estimate a variety of effects: the increase in click rate due to the repositioning of a banner, the impact on subscription rate as a consequence of a discount or special
Related content
-
September 19, 2023The new Fulfillment by Amazon system empowers sellers to have more transparency and control over their capacity within Amazon’s fullfilment network by applying market-based principles. -
June 22, 2023Kanoria and coauthors honored for their paper narrowing the gap between theoretical understanding and practical experience in matching markets.
-
June 02, 2023In a plenary talk, the Berkeley professor and Distinguished Amazon Scholar will argue that AI research should borrow concepts from economics and focus on social collectives.
-
April 14, 2023The requirement that at any given time, all customers see the same prices for the same products necessitates innovation in the design of A/B experiments.
-
February 28, 2023How the former astrobiology professor is charting new territory as a scientist for Amazon Flex.
-
Courtesy of Pai-Ling YinFebruary 08, 2023How her background helps her manage a team charged with assisting internal partners to answer questions about the economic impacts of their decisions.
-
December 09, 2022Amazon provided funding for two-week workshop led by Nobel Prize winner Thomas Sargent.
-
Courtesy of Texas A&MOctober 17, 2022Tatevik Sekhposyan, Amazon Scholar and Texas A&M University professor, enjoys the flexibility of economics and how embracing uncertainty can enhance prediction.
-
September 13, 2022Paper introduces a unified view of the learning-to-bid problem and presents AuctionGym, a simulation environment that enables reproducible validation of new solutions.
-
August 05, 2022How the Amazon Supply Chain Optimization Technologies principal economist uses his expertise in time series econometrics to forecast aggregate demand.
-
June 23, 2022Two-day RecSys workshop that extends the popular REVEAL to include CONSEQUENCES features Amazon organizers, speakers.
-
May 16, 2022Matt Taddy, vice president of Amazon’s Private Brands business, is the coauthor of Modern Business Analytics: Practical Data Science for Decision Making, a primer for those who want to gain the skills to use data science to help make decisions in business and beyond.
-
March 22, 2022Amazon Scholar Alexandre Belloni discusses the implications of auction design on digital goods.
-
January 07, 2022Amazon Scholar David Card and Amazon academic research consultant Guido Imbens talk about the past and future of empirical economics.
-
Dave BurbankDecember 13, 2021Amazon Research Award recipient Éva Tardos studies complex theoretical questions that have far-ranging practical consequences.
-
November 17, 2021The paper by Özer and his co-authors examines the role of earmarking and transparency on donors and their donations.
-
Credits: GENEVIEVE SHIFFRAR (Card); Stanford University (Imbens)October 13, 2021Amazon Scholar David Card wins half the award, while academic research consultant Guido Imbens shares in the other half.
-
September 01, 2021Amazon’s scientists have developed a variety of scientific models to help customers get the most out of their membership.
-
Glynis CondonJuly 26, 2021In a paper published at INFORMS in 2020, the Amazon senior principal scientist and his co-authors factored in both revenue and "the expected utility to the customer from the purchase."
-
July 20, 2021The senior economist knows what it means to pursue a career path like hers, and she’s determined to help others along the way.
-
Courtesy of Muthoni NgatiaMay 03, 2021The Amazon economist says lessons from her mother taught her a lot about how the world works, and why economics plays such a vital role.
