Song Yao
Song Yao

MARKETING
Assistant Professor of Marketing

Print Overview

Song Yao is an Assistant Professor of Marketing and the McManus Research Chair at the Kellogg School of Management, Northwestern University. Professor Yao has won the Paul Green Best Paper Award and the John Howard Dissertation Award, both of which are sponsored by the American Marketing Association. He was also the finalist for the Frank Bass Outstanding Dissertation Award in 2011 and 2012, and the John Little Best Paper Award in 2009 and 2011.

Professor Yao's research interests include quantitative marketing, online marketing, auctions, pricing, competitive strategy, and customer management. With a methodological and theoretical orientation of empirical microeconomics, his substantive research focuses on network effects, especially in the context of new media such as online retailing and online advertising. His publications appear in leading academic journals, including Marketing Science.

Professor Yao teaches the MBA elective "Customer Analytics" at the Kellogg School of Management. He also taught the PhD course "Introduction to Applied Econometrics II." Prior to joining Kellogg, he taught Marketing Management at Duke University.

Professor Yao received his Ph.D. in Business Administration from Duke University, M.A. in Economics from the University of California, Los Angeles, and B.A. in Economics from Renmin University of China.



  • Recent Media Coverage

    The Economist Intelligence Unit: Increasing Revenue from Online Auctions—Buyer-seller interactions affect customer value in two-sided markets

    Financial Times: Something for the weekend

    See all Kellogg in the Media
Print Vita
Education
PhD, 2009, Marketing, Duke University
MA, 2004, Economics, University of California, Los Angeles
CPhil, 2003, Economics, University of California, Los Angeles
BA, 1999, Economics, Renmin University of China, Beijing

Academic Positions
Assistant Professor, Marketing, Kellogg School of Management, Northwestern University, 2009-present

Grants and Awards
Finalist, John D.C. Little Best Paper Award, INFORMS, 2009
AMA John A. Howard Award for "A Dynamic Model of Sponsored Search Advertising", 2009
Faculty Impact Award for MBA teaching Excellence, 2010
Finalist, John D.C. Little Best Paper Award, Marketing/Management Science, 2011
Finalist, Frank M. Bass Dissertation Paper Award, INFORMS, 2011
Finalist, Frank M. Bass Dissertation Paper Award, INFORMS, 2012
Paul Green Best Paper Award, American Marketing Association, 2012
Management Science Meritorious Service Award, INFORMS, 2013
McManus Faculty Research Chair, Northwestern University, 2012-2013, 2014-2015

Editorial Positions
Editorial Board Member, Journal of Marketing Research
Ad-hoc Reviewer, Management Science
Ad-hoc Reviewer, Marketing Science
Ad-hoc Reviewer, Journal of Economics and Management Strategy
Ad-hoc Reviewer, Operations Research
Ad-hoc Reviewer, Review of Marketing Research
Ad-hoc Reviewer, Social Sciences and Humanities Research Council of Canada (SSHRC)

Print Research
Research Interests
Quantitative Marketing; Empirical IO; Online Marketing; Auctions; Competitive Strategy; Customer Management

Articles
Lambrecht, Anja, Avi Goldfarb, Randall Lewis, Anita Rao, Navdeep Sahni and Song Yao. 2014. How Do Firms Make Money Online?. Marketing Letters.
Yao, Song, Carl F. Mela, Jeongwen Chiang and Yuxin Chen. 2012. Determining Consumers' Discount Rates With Field Studies. Journal of Marketing Research. 49(6): 822-841.
Yao, Song and Carl F. Mela. 2011. A Dynamic Model of Sponsored Search Advertising. Marketing Science. 30: 447-468.
Yao, Song and Carl F. Mela. 2009. Sponsored Search Auctions: Research Opportunities in Marketing. Foundations and Trends in Marketing. 3(2): 75-126.
Yao, Song and Carl F. Mela. 2008. Online Auction Demand. Marketing Science. 27(5): 861-885.
Working Papers
Yao, Song, Yuxin Chen and Wenbo Wang. 2015. Channel Search and Welfare Implications of Commercial Breaks.
Chen, Yuxin and Song Yao. 2015. Sequential Search with Refinement: Model and Application with Click-stream Data.

 
Print Teaching
Doctoral
Introduction to Applied Econometrics II (MECS-477-0)
Develops a practical econometrics toolkit and an integrated approach for the use of statistical methods for doctoral research in the management sciences. Prerequisites: ECON 476.

Full-Time / Part-Time MBA
Customer Analytics (MKTG-953-0)
Marketing is evolving from an art to a science. Many firms have extensive information about consumers' choices and how they react to marketing campaigns, but few firms have the expertise to intelligently act on such information. In this course, students will learn the scientific approach to marketing with hands-on use of technologies such as databases, analytics and computing systems to collect, analyze, and act on customer information. While students will employ quantitative methods in the course, the goal is not to produce experts in statistics; rather, students will gain the competency to interact with and manage a marketing analytics team.