Michael Braun
![Michael Braun](/-/media/Site/Cox/Faculty/Photo/Profile/Linked/Michael-Braun.jpg?h=2200&iar=0&w=1464&hash=0DC17FCA1CA76794D61D2D378374A527)
Tenure and Tenure-Track Faculty
Associate Professor, Marilyn and Leo F. Corrigan Research Professor
Marketing
Phone |
214-768-3965 |
Office |
Fincher 309 |
CV |
Education
PhD, Operation & Information Management, University of Pennsylvania
Biography
Michael Braun, Associate Professor of Marketing at the Cox School of Business, joined the SMU community in 2013 after seven years on the faculty of the MIT Sloan School of Management. The core of his research is the statistical analysis of large and complex customer databases, with an emphasis on customer lifetime value, advertising effectives, and public policy issues. He has written on, spoken on, and taught about management topics such as sales forecasting, customer retention and valuation, marketing ROI, social networking models, segmentation and targeting strategies, online advertising and insurance decisions. Professor Braun’s work has been published in top academic publications such as Marketing Science, Management Science, and the Journal of the American Statistical Association, and he is a member of the Marketing Science Editorial Review Board. He has held several leadership positions for the American Statistical Association's Section on Statistics and Marketing, including Section Chair in 2011 and Program Chair in 2009, 2013 and 2015. In addition, he is the author of four software packages for the R statistical computing language. Professor Braun’s teaching interests are to train the next generation of business leaders on how to analyze, interpret and use marketing data to address real-world managerial problems. He takes a hands-on approach with his classes, believing that managers cannot effectively act on the volumes of customer data that they collect, unless they master a foundational set of quantitative, statistical tools. He teaches the Managerial Statistics in the Cox School’s M.B.A. and other graduate management programs, as well as Customer Analytics Using Probability Models in the M.S. in Business Analytics program. Michael Braun earned his Ph.D. from the Wharton School of the University of Pennsylvania. He holds an A.B. with Honors in Economics from Princeton University, and an M.B.A. from the Fuqua School of Business at Duke University. Before entering academia, he worked on the development and deployment of broadband Internet products for such companies as Comcast, Marcus Cable and Charter Communications. From 1999 to 2002, he was Vice President for Global Affiliate Operations of Chello Broadband, the Amsterdam-based Internet arm of United Pan-Europe Communications. He also worked as a production assistant at ESPN, and as a researcher for NBC at the 1992 Summer Olympics in Barcelona.
Teaching
MAST 6252 Applied Predictive Analytics II
MNGT 6210 Global Leadership Program
Research
Customer loyalty, retention, and lifetime value
Empirical analysis of legal and policy issues
Advertising targeting and response
Bayesian methods and computation for marketing research and analytics
Publications
Braun, Michael, Bart De Langhe, Stefano Puntoni, and Eric Schwartz (2024). “Leveraging Digital Advertising Platforms for Consumer Research.” Journal of Consumer Research, 50. https://doi.org/10.1093/jcr/ucad058
Braun, Michael (2024). “Revisiting Scalable Targeted Marketing with Distributed Markov Chain Monte Carlo.” Journal of Marketing Research. Accepted for publication.
Turner, Jenia Iontcheva, Ronald Wright, and Michael Braun (2024). “Neglected Discovery.” Duke Law Journal, 73(6): 1173–1228. https://scholarship.law.duke.edu/dlj/vol73/iss6/1 .
Braun, Michael, Jeremy Rosenthal, and Kyle Therrian (2018). “Police Discretion and Racial Disparity in Organized Retail Theft Arrests: Evidence from Texas.” Journal of Empirical Legal Studies, 15(4). https://rdcu.be/8vJZ
Braun, Michael (2017). “sparseHessianFD: Estimating Sparse Hessian Matrices in R.” Journal of Statistical Software, 82(10):1–22. https://doi.org/10.18637/jss.v082.i10.
Braun, Michael and Paul Damien (2016). “Scalable Rejection Sampling for Bayesian Hierarchical Models.” Marketing Science, 35(3):427–444. https://doi.org/10/b4bd.
Braun, Michael, David A. Schweidel, and Eli M. Stein (2015). “Transaction Attributes and Customer Valuation.” Journal of Marketing Research, 52(6):848–864. https://doi.org/10/b4bb .
Braun, Michael (2014). “trustOptim: An R Package for Trust Region Optimization with Sparse Hessians.” Journal of Statistical Software, 60(4):1–16. https://doi.org/10/b4bc
Braun, Michael and Wendy W. Moe (2013). “Online Display Advertising: Modeling the Effects of Multiple Creatives and Individual Impression Histories.” Marketing Science, 32(5):753–767. https://doi.org/10/b4bf
Braun, Michael and David A. Schweidel (2011). “Modeling Customer Lifetimes with Multiple Causes of Churn.” Marketing Science, 30(5):881–902. https://doi.org/10/ddv975
Working Papers
Braun, Michael and Eric M. Schwartz (2024). "Where A-B Testing Goes Wrong: How Divergent Delivery Affects What Online Experiments Cannot (and Can) Tell You About How Customers Respond to Advertising.” https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3896024
Braun, Michael, Jenia I. Turner, and Ronald F. Wright (2024). "Defense Use of Digital Discovery in Criminal Cases: A Quantitative Analysis.”
Braun, Michael (2018) sparseMVN: An R Package for Multivariate Normal Functions with Sparse Covariance and Precision Matrices. https://braunm.github.io/sparseMVN/ .