About Me:

I am an Assistant Professor of Marketing at the Wharton School of the University of Pennsylvania. My research explores how machine learning and Bayesian statistical methodologies can solve real world marketing problems. At Wharton, I teach the class Data and Analysis for Marketing Decisions, for which I was awarded the Wharton Teaching Excellence award in 2019.

Interested in my research or in collaborating? Feel free to email me at ryandew@wharton.upenn.edu. You can also find me on LinkedIn and on Google Scholar.

For more about my background, check out my CV.

Research Overview:

I study how modern statistical and computational methods can enhance the capacity of marketing managers to make data-driven decisions. I am particularly interested in topics in marketing analytics, customer relationship management, and preference measurement, with a focus on understanding dynamics in consumer purchasing patterns. I am also interested in incorporating visual and textual data into marketing models, with a specific interest in understanding the interplay between the stated and visual identities of brands, and in bringing big data to bear on firms' design decisions. Methodologically, I focus on techniques from machine learning, Bayesian nonparametrics, and Bayesian econometrics. I'm honored to have received several awards for my research, including the 2018 INFORMS Society for Marketing Science Doctoral Dissertation Award, and the 2018 Marketing Section of the American Statistical Association's Doctoral Research Award.

  • Bayesian Nonparametric Customer Base Analysis with Model-based Visualizations
    Ryan Dew and Asim Ansari
    Marketing Science, 2018
    [Show Abstract] [Paper] [Code Notebook] [Replication Data] [Stan Code]

  • Modeling Dynamic Heterogeneity using Gaussian Processes
    Ryan Dew, Asim Ansari, Yang Li
    Journal of Marketing Research, 2020
    [Show Abstract] [Paper]

Working Papers:
  • Letting Logos Speak: Leveraging Multiview Representation Learning for Data-Driven Logo Design
    Ryan Dew, Asim Ansari, Olivier Toubia
    [Show Abstract] [Working Paper] [Explore Our Data] [Personality-based Logo Generator]

Research in Progress:
  • Detecting Routines In Ride-sharing: Implications For Customer Management
    Ryan Dew, Eva Ascarza, Oded Netzer, and Nachum Sicherman
  • [Show Abstract]

  • Preference Measurement with Unstructured Data, with Applications to Adaptive Onboarding Surveys
    Ryan Dew
  • [Show Abstract]

  • A General, Kernel-based Framework for Capturing Cross-Category Choice Dynamics
    Ryan Dew and Yuhao Fan
  • [Show Abstract]

  • The Impact of a Free Cancellation Program on Customer Booking Behavior and Firm Performance
    Yuhao Fan, Ryan Dew, Eric T. Bradlow, Peter Fader
  • [Show Abstract]

  • Dynamic Contextual Recommendation Systems
    Joint work with Yegor Tkachenko and Asim Ansari
    [Show Abstract]

  • Customer-Centric Data Fusion
    Joint work with Oded Netzer
    [Show Abstract]