Elea Feit, PhD

Candid photo of Elea Feit

Elea McDonnell Feit’s research focuses on leveraging customer data to make better product design and advertising decisions, particularly when data is incomplete, unmatched or aggregated. Much of her career has focused on developing new quantitative methods and bringing them into practice, first working in product design at General Motors, then commercializing new methods at the marketing analytics firm,The Modellers, and most recently as the Executive Director of the Wharton Customer Analytics Initiative, where she built the academic-industry partnership program. She brings a rich understanding of industry problems to her research, which has been published in top-tier journals including Marketing Science, Management Science and the Journal of Marketing Research. She enjoys making analytics accessible to a broad audience and regularly teaches popular tutorials and workshops for practitioners on marketing experiments, marketing analytics in R, and measuring advertising response. At LeBow, she has developed courses in data-driven digital marketing (undergrad), marketing experiments (masters) and Bayesian and causal inference (doctoral). She is co-author of R for Marketing Research and Analytics, which has been translated to Chinese, Japanese and Korean and adapted to Python. She holds a PhD in Marketing from the University of Michigan, an MS in Industrial Engineering from Lehigh University and a BA in Mathematics from University of Pennsylvania.

Areas of Expertise

  • Advertising Attribution
  • Advertising Incrementality
  • Bayesian Decision Theory
  • Bayesian Hierarchical Models
  • Data Fusion
  • Missing Data
  • Product Design

Selected Works

Articles

Helveston, John, Feit, Elea M., and Michalek, Jeremy, Pooling Revealed and Stated Preferences in the Presence of RP Endogeneity. Transportation Research 109 (Feb 2018): 70-89.

Dotson, Jeffrey, Fan, Rachel, Feit, Elea M., Oldham, Jeffrey, and Yeh, Yi-Shen, Brand Attitudes and Search Engine Queries. Journal of Interactive Marketing 37 (Feb 2017): 105-116.

Zantedeschi, Daniel, Feit, Elea M., and Bradlow, Eric T., Measuring Multi-Channel Advertising Effectiveness. Management Science 63 (Aug 2017): 2706-2728.

Ada, Sila, Abou Nabout, Nadia, and Feit, Elea M., Context Information Can Increase Revenue in Online Display Ad Auctions: Evidence from a Policy Change. Journal of Marketing Research (Mar 2022):

Feinberg, Fred, Bruch, Elizabeth, Braun, Michael, Falk, Brett, Fefferman, Nina, Feit, Elea M., Helveston, John, Larrenmore, Daniel, McShane, Blakeley, Patania, Alice, and Small, Mario, Choices in Networks: A Research Framework. Marketing Letters 31 (Sep 2020): 349-359.

Han, Jung Ah, Feit, Elea M., and Srinivasan, Shuba, Negative buzz can increase awareness and purchase intent. Marketing Letters 31 (Nov 2019): 89-104.

Feit, Elea M., and Berman, Ron, Test and Roll: Profit-Maximizing A/B Tests. Marketing Science 38 (Nov 2019): 913-1084.

Haaf, Grace, Azevedo, Ines, Morrow, Ross, Feit, Elea M., and Michalek, Jeremy, Forecasting light-duty vehicle demand using alternative-specific constants for endogeneity correction versus calibration. Transportation Research 84 (Feb 2016): 182-210.

Helveston, John, Liu, Yi, Feit, Elea M., Fuchs, Erica, Klampfl, Erica, and Michalek, Jeremy, Will Subsidies Drive Electric Vehicle Adoption? Measuring Consumer Preferences in the U.S. and China. Transportation Research 73 (Mar 2015): 96-112.

Feit, Elea M., Wang, Pengyuan, Bradlow, Eric T., and Fader, Peter S., Fusing Aggregate and Disaggregate Data with an Application to Multi-Platform Media Consumption. Journal of Marketing Research 50 (Jun 2013): 348-364.

Feit, Elea M., Beltramo, Mark, and Feinberg, Fred, Reality Check: Combining survey and market data to estimate choice models. Management Science 56 (Mar 2010): 785-800.

Netzer, Oded, Toubia, Olivier, Bradlow, Eric T., Dahan, Ely, Evgeniou, T., Feinberg, Fred, Feit, Elea M., Hui, Sam, Johnson, J., Liechty, John C., Orlin, J.B., and Rao, Vithala, Beyond Conjoint Analysis: Advances in preference meaasurement. Marketing Letters 19 (Jul 2008): 337-354.

Books

Schwartz, Jason, Chapman, Chris, and Feit, Elea M., Python for Marketing Research and Analytics. New York: Springer, (2020):

Chapman, Chris, and Feit, Elea M., R for Marketing Research and Analytics. New York: Springer, (2019):

Chapters

Papies, Dominik, Ebbes, Peter, and Feit, Elea M., “Endogeneity and Causal Inference in Marketing.” History of Marketing Science, Ed. Russ Wiener and Scott A. Neslin. US: NOW Publishers, (2022): 25.

Feit, Elea M., and Bradlow, Eric T., “Fusion Modeling.” Handbook of Marketing Research, Ed. Homburg, Klarmann and Vomberg. Berlin: Springer, (2019):

Feit, Elea M., Feinberg, Fred, and Lenk, Peter, “Bayesian Analysis.” Advanced Methods for Modeling Markets, Ed. Leeflang, Wieringa, Bijmolt and Pauwels. New York: Springer, (2017):

Editorial Board Service

International Journal of Research in Marketing – Member (2020)
Journal of Marketing Research – Associate Editor (2020)
Marketing Science – Guest Associate Editor (2020)
Quantitative Marketing and Economics – Associate Editor (2020)

Education

BA Mathematics - University of Pennsylvania Philadelphia, PA USA 1994
MS Operations Research - Lehigh University Bethelehem , PA USA 1998
PhD Marketing - University of Michigan Ann Arbor, MI USA 2009

Awards

2020 Top Analytics Educator Award (Digital Analytics Association)
2018 Allen Rothwarf Award for Teaching Excellence (Drexel University)
2017 Data Science Research Award ($25,000) (Adobe)
2017 Best Software Demo Award (American Marketing Association ART Forum)
2016 Excellence in Research Award (LeBow College of Business)
2016 Junior Teaching Award (LeBow College of Business)
2013 4 under 40 Award (American Marketing Association)

Media Mentions

Rooting for Marketing Research

via Research World

Elea Feit, assistant professor of marketing, is highlighted for her research and development of the “test and roll” method for A/B tests that optimize sample size, creating marketing tools that can serve as risk management for companies.

Data Science Is The Key To Marketing ROI - Here's How To Nail It

via Forbes

Assistant Professor of Marketing Elea Feit highlights how data analytics can be used to assess the effectiveness of new marketing strategies.

Drexel professor teamed up with Google for research project. Here's what they found out.

via Philadelphia Business Journal

Research by assistant professor of marketing Elea McDonnell Feit and co-authors on the relationship between Google search results and brand reputation is covered in the Philadelphia Business Journal.

College News

Elea McDonnell Feit’s paper in the Journal of Marketing Research analyzes the effects of a policy change at one of Europe’s leading advertising exchanges.

In early March, LeBow graduate students teamed up to solve a crisis scenario designed by The GIANT Company.

Assistant Professor of Marketing Elea Feit won a $25,000 grant from Adobe’s University Marketing Research Awards Program for her research into improving A/B testing methods.