Homepage of Eric M. Schwartz

Last updated 2026-04-06

Eric Schwartz faculty photo
Curriculum Vitae (HTML) | Curriculum Vitae (PDF)

Welcome to Eric Schwartz's simple website!

Eric Schwartz is an Associate Professor of Marketing, with tenure, at the Stephen M. Ross School of Business at the University of Michigan. He is a data scientist applying research in statistics, machine learning, and econometrics to a range of problems. These span problems in customer analytics for marketing, such as A/B testing methods, native advertising, streaming media, and valuing customers, as well as in optimal resource allocation for public health. In the classroom, Professor Schwartz focuses on the quantitative aspects of marketing, including electives on customer lifetime value and customer analytics, as well as the introductory core marketing course. He is also co-founder and board member of BlueConduit, a social venture spun out of the University of Michigan applying machine learning research developed during the Flint Water Crisis to find lead pipes for cities and utilities across North America. For more biographical information, see below.

What's New

Research and Publications

Journal Publications

  1. Braun, Michael, and Eric M. Schwartz (2025). Where A/B Testing Goes Wrong: How Divergent Delivery Affects What Online Experiments Cannot (and Can) Tell You About How Customers Respond to Advertising. Journal of Marketing, 89(2), 71–95. Journal Link. PDF. BibTeX.

  2. Braun, Michael, Bart de Langhe, Stefano Puntoni, and Eric M. Schwartz (2024). Leveraging Digital Advertising Platforms for Consumer Research. Journal of Consumer Research, 51(1), 119–128. Journal Link.

  3. Aribarg, Anocha and Eric M. Schwartz (2020). Native advertising in online news: Tradeoffs among clicks, brand recognition and website trustworthiness, Journal of Marketing Research, 57(1), 20–24. Journal Link. PDF. BibTeX.

  4. Proserpio, D., J. R. Hauser, X. Liu, T. Amano, A. Burnap, T. Guo, D. Lee, R. A. Lewis, K. Misra, Eric M. Schwartz, A. Timoshenko, L. Xu, and H. Yoganarasimhan (2020). Soul and Machine (Learning). Marketing Letters, 31(4), Special Issue for 11th Triennial Invitational Choice Symposium, 393–404. Journal Link.

  5. Misra, Kanishka, Eric M. Schwartz, Jacob D. Abernethy (2019). Dynamic online pricing with incomplete information using multi-armed bandit experiments. Marketing Science, 38(2), 226–252. Journal Link. PDF. BibTeX.

  6. Schwartz, Eric M., Eric T. Bradlow, and Peter S. Fader (2017). Customer acquisition via display advertising using multi-armed bandit experiments. Marketing Science, 36(4), 500–522. Journal Link. PDF. BibTeX.

  7. Schwartz, Eric M., Eric T. Bradlow, and Peter S. Fader (2014). Model selection using database characteristics: Developing a classification tree for longitudinal incidence data. Marketing Science, 33(2), 188–205. Journal Link. PDF. BibTeX. Press Release.

  8. Berger, Jonah, and Eric M. Schwartz (2011). What drives immediate and ongoing word of mouth? Journal of Marketing Research, 48 (5), 869–880. Journal Link. PDF. BibTeX. Featured in Contagious .

Working Papers

Work in Progress

Peer-Reviewed Conference Proceedings Papers

Other Conference Proceedings

Teaching

Current and recent courses
Past courses
Executive education
Teaching interests
Teaching materials developed

Press and Media

About Me

Employment and Education

Employment Education

Bio

Eric Schwartz is an Associate Professor of Marketing (with tenure) at the Stephen M. Ross School of Business at the University of Michigan. Professor Schwartz's expertise focuses on predicting customer behavior, understanding its drivers, and examining how firms actively acquire customers and manage their relationships through interactive marketing experiments and adaptive data collection. His current projects aim to optimize firms' A/B testing and adaptive marketing experiments using a multi-armed bandit framework, often working with companies and organizations. His broader research in customer analytics stretches across managerial applications, including online experiments, online advertising, dynamic pricing, native advertising, streaming video binge viewing, and word-of-mouth. The quantitative methods he uses are primarily machine learning, active learning, Bayesian statistics, and field experiments. Applying those same methods elsewhere, he also works on public policy problems focused on health and safety. His work has been recognized with multiple awards, including the AMA Robert J. Lavidge Global Marketing Research Award, finalist for the AMA Shelby D. Hunt/Harold H. Maynard Award, finalist for the AMA/MSI/H. Paul Root Award, ISMS John D. C. Little Best Paper Award winner, finalist for the Paul E. Green Award, and KDD Applied Data Science Best Student Paper Award. He is a member of the Editorial Review Board of Marketing Science. At Ross, he was the Arnold M. and Linda T. Jacob Faculty Fellow 2018–19. He is also co-founder and board member of BlueConduit, which provides data science software to identify homes with hazardous lead drinking water pipes for water utilities spanning 300 cities and towns in the US and Canada. Before joining the Michigan Ross faculty in 2013, Professor Schwartz earned his Ph.D. in Marketing from the Wharton School and a B.A. in Mathematics and Hispanic Studies, all from the University of Pennsylvania.

BibTeX Citations

@article{braunschwartz2025abtesting,
title={Where A/B Testing Goes Wrong: How Divergent Delivery Affects What Online Experiments Cannot (and Can) Tell You About How Customers Respond to Advertising},
author={Braun, Michael and Schwartz, Eric M},
journal={Journal of Marketing},
volume={89},
number={2},
pages={71--95},
year={2025}
}

@article{braunetal2024digad,
title={Leveraging Digital Advertising Platforms for Consumer Research},
author={Braun, Michael and de Langhe, Bart and Puntoni, Stefano and Schwartz, Eric M},
journal={Journal of Consumer Research},
volume={51},
number={1},
pages={119--128},
year={2024}
}

@article{aribargschwartz2020native,
title={Native Advertising in Online News: Trade-Offs Among Clicks, Brand Recognition, and Website Trustworthiness},
author={Aribarg, Anocha and Schwartz, Eric M},
journal={Journal of Marketing Research},
volume={57},
number={1},
pages={20--34},
year={2020}
}

@article{misraetal2019banditpricing,
title={Dynamic Online Pricing with Incomplete Information Using Multi-Armed Bandit Experiments},
author={Misra, Kanishka and Schwartz, Eric M and Abernethy, Jacob D},
journal={Marketing Science},
volume={38},
number={2},
pages={226--252},
year={2019},
publisher={INFORMS}
}

@article{schwartzetal2017bandit,
title={Customer acquisition via display advertising using multi-armed bandit experiments},
author={Schwartz, Eric M and Bradlow, Eric T and Fader, Peter S},
journal={Marketing Science},
volume={36},
number={4},
pages={500--522},
year={2017},
publisher={INFORMS}
}

@article{schwartzetal2014hmmrf,
title={Model selection using database characteristics: Developing a classification tree for longitudinal incidence data},
author={Schwartz, Eric M and Bradlow, Eric T and Fader, Peter S},
journal={Marketing Science},
volume={33},
number={2},
pages={188--205},
year={2014},
publisher={INFORMS}
}

@article{bergerschwartz2011wom,
title={What drives immediate and ongoing word of mouth?},
author={Berger, Jonah and Schwartz, Eric M},
journal={Journal of Marketing Research},
volume={48},
number={5},
pages={869--880},
year={2011},
publisher={American Marketing Association}
}

(End)

This page was typed by hand and written in HyperText Markup Language (HTML). That means Web 1.0, 1990s style, without any fancy apps and slick Web 2.0 style graphics. No WhatYouSeeIsWhatYouGet editors are needed. This is a flat website in a single page. You can see all contents with full transparency with Show Page Source / Inspect Element in your browser. I used the template provided by Frank da Cruz.
~ Eric Schwartz ~