Research

My research focuses on performance-based marketing and new product development. I build on the methods from statistics, computer science, and operations research to propose solutions to important business problems. My projects aim for managerial relevance and academic rigor.

Featured Publications

A Sample Size Calculation for Training and Certifying Targeting Policies
Management Science (forthcoming) with Duncan Simester and Spyros I. Zoumpoulis

How Retailers Became Ad Platforms
Harvard Business Review (2024) with Sebastian Gabel and Duncan Simester

Product Aesthetic Design: A Machine Learning Augmentation
Marketing Science (2023) with Alex Burnap and John R. Hauser

Product Choice with Large Assortments: A Scalable Deep-Learning Model
Management Science (2022) with Sebastian Gabel

Efficiently Evaluating Targeting Policies: Improving on Champion vs. Challenger Experiments
Management Science (2020) with Duncan Simester and Spyros I. Zoumpoulis

Targeting Prospective Customers: Robustness of Machine Learning Methods to Typical Data Challenges
Management Science (2020) with Duncan Simester and Spyros I. Zoumpoulis

Identifying Customer Needs from User-Generated Content
Marketing Science (2019) with John R. Hauser

Is Deep Learning a Game Changer for Marketing Analytics?
MIT Sloan Management Review (2019) with Glen Urban, Paramveer Dhillon, and John R. Hauser

Working Papers

In-Store Coupons: A Large-Scale Field Experiment
with Sebastian Gabel and Duncan Simester

Can Large Language Models Extract Customer Needs as well as Professional Analysts?
with Chengfeng Mao and John R. Hauser

Transfer Learning for Targeted Marketing: A Bayesian Matrix Factorization Approach
with Marat Ibragimov and Duncan Simester