Join Wharton Marketing Professor and Faculty Co-Director of WCAI, Eric Bradlow, at Zillow for our Seattle Alumni Event.

The event will feature a presentation from Professor Bradlow on his research about inferring individual-level behavior from aggregate data.  This will be followed by networking opportunities.

Agenda
5:00 PM – 5:30 PM: Registration
5:30 PM – 6:45 PM: Presentation
6:45 PM – 8:00 PM: Networking Reception

Details
Zillow Headquarters is located at 1301 2nd Ave, Seattle, WA 98101

Who has the remote?

Television became commonplace in the 1950’s and revolutionized the way public opinion was influenced. It was, and continues to be, one of the primary mediums to reach audiences. But for marketers, it’s difficult to extract meaningful customer-level data.

As data analysis and technology develop, businesses can make better decisions informed by predicting customer behavior from individual-level data. The problem with television data — despite providers’ claims — is that it usually comes at the household or aggregate level leaving firms wondering, “who has the remote?”

In this presentation, Professor Bradlow will discuss different but related examples that provide new methods to handle data aggregation challenges:

  • Data from household-level TV viewing and inferring “Who is watching the TV?”
  • Data from aggregate distribution of marketing and inferring “Who got the coupon?”
  • Data from multi-platform online consumption and aggregate TV ratings and inferring “Which online users are the TV watchers?”

$10 for Wharton Club of Seattle members – use discount code WCAIMEMBER upon registration
$25 for non-members
This event is for Penn Alumni only.*

*If you are a current student and would like to attend, please reach out to wcai-events@wharton.upenn.edu

Register here! 


About Eric Bradlow

Professor Eric T. Bradlow is the K.P. Chao Professor, Professor of Marketing, Statistics and Education, Vice-Dean and Director of Wharton Doctoral Programs, and Co-Director of the Wharton Customer Analytics Initiative. An applied statistician, Professor Bradlow uses high-powered statistical models to solve problems on everything from Internet search engines to product assortment issues. Specifically, his research interests include Bayesian modeling, statistical computing, and developing new methodology for unique data structures with application to business problems.

Eric was recently named a fellow of the American Statistical Association, American Educational Research Association, is past chair of the American Statistical Association Section on Statistics in Marketing, is a statistical fellow of Bell Labs, and was named DuPont Corporation’s best young researcher while working there in 1992.

A prolific scholar, Professor Bradlow’s research has been published in top-tier academic journals such as the Journal of the American Statistical Association, Psychometrika, Statistica Sinica, Chance, Marketing Science, Management Science, and Journal of Marketing Research. He also serves as Associate Editor for the Journal of Computational and Graphical Statistics, the Journal of Educational and Behavioral Statistics, Marketing Science and Psychometrika and is on the Editorial Boards of Marketing Letters, Marketing Science, Journal of Marketing Research, Quantitative Marketing and Economics, and the Quarterly Journal of Electronic Commerce.

Professor Bradlow has won numerous teaching awards at Wharton, including the MBA Core Curriculum teaching award, the Miller-Sherrerd MBA Core Teaching award and the Excellence in Teaching Award. His teaching interests include courses in Statistics, Marketing Research, Marketing Management and PHD Data Analysis, as well as Essentials of Marketing for Wharton’s Executive MBA program. Professor Bradlow earned his PhD and Master’s degrees in Mathematical Statistics from Harvard University and his BS in Economics from the University of Pennsylvania.

RESEARCH INTERESTS

  • Probability models for Marketing data
  • Applied Bayesian modeling
  • Missing data problems
  • Choice modeling
  • Statistical models for unique data structures

MORE ABOUT ERIC

Read more on published works, courses, and awards on Wharton’s marketing site