About

Ilya Morozov is an Associate Professor of Marketing at the Kellogg School of Management, Northwestern University. His research focuses on marketing strategy in contexts where consumers have limited knowledge about existing products, do not notice new product launches, and spend little time learning about available alternatives. His recent work combines machine learning tools, field experiments, and rigorous economic models to improve personalized product recommendations and optimize the design of online platforms. Professor Morozov holds a Ph.D. in Quantitative Marketing from Stanford Graduate School of Business, an M.Sc. in Economics and Finance from the Center for Monetary and Financial Studies (CEMFI) in Madrid, and a BA in Economics from the Higher School of Economics (HSE) in Moscow.

Research topics

• Computer Science
• Marketing
• Econometrics
• Microeconomics
• Business
• Economics

Selected publications

• The Promotional Effects of Live Streams by Twitch Influencers

  Marketing Science · 2025-02-20 · 11 citations

  articleSenior author

  Live streaming of video games has a small and positive effect on consumers’ usage and purchases of these games, suggesting that most games do not profit from sponsoring live streams by influencers.

  PublisherDOI

• Demand Estimation with Text and Image Data

  arXiv (Cornell University) · 2025-03-26

  preprintOpen access

  We propose a demand estimation approach that leverages unstructured data to infer substitution patterns. Using pre-trained deep learning models, we extract embeddings from product images and textual descriptions and incorporate them into a mixed logit demand model. This approach enables demand estimation even when researchers lack data on product attributes or when consumers value hard-to-quantify attributes such as visual design. Using a choice experiment, we show this approach substantially outperforms standard attribute-based models at counterfactual predictions of second choices. We also apply it to 40 product categories offered on Amazon.com and consistently find that unstructured data are informative about substitution patterns.

  PublisherOA PDFDOI

• Space Exploration

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Where Does Advertising Content Lead You? We Created a Bookstore to Find Out

  Marketing Science · 2024-04-26 · 13 citations

  article1st authorCorresponding

  We conduct an experiment in a simulated online bookstore to study how consumers respond to display ads with varied content.

  PublisherDOI

• Spatial Search: Experimental Evidence

  AEA Randomized Controlled Trials · 2024-06-07

  dataset1st authorCorresponding
  PublisherDOI

• Spatial Search: Experimental Evidence

  AEA Randomized Controlled Trials · 2024-06-07

  dataset1st authorCorresponding
  PublisherDOI

• Demand Estimation with Text and Image Data

  SSRN Electronic Journal · 2023-01-01 · 2 citations

  articleOpen access
  PublisherDOI

• Welfare Effects of Personalized Rankings

  Marketing Science · 2023-05-15 · 36 citations

  articleSenior author

  The effect of personalized ranking in online retail on consumer welfare.

  PublisherDOI

• Demand Estimation with Text and Image Data

  SSRN Electronic Journal · 2023-01-01 · 7 citations

  articleOpen access
  PublisherDOI

• Make Every Second Count: Time Allocation in Online Shopping

  SSRN Electronic Journal · 2023-01-01 · 4 citations

  articleOpen accessSenior author
  PublisherDOI

Frequent coauthors

• Stephan Seiler

  20 shared

• Liwen Hou

  17 shared

• Xiaojing Dong

  17 shared

• Stephan Seiler

  Centre for Economic Policy Research

  3 shared

• Ayush Kanodia

  Motilal Nehru National Institute of Technology

  2 shared

• Elena Podkolzina

  2 shared

• Robert Donnelly

  2 shared

• Giovanni Compiani

  University of Chicago

  2 shared