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Fall 2022 Data Science Seminar Series: Fernando Luco: Tracking Consumers: The Trade-off Between the Value of Granular Data and Consumers’ Privacy

November 28, 2022

2:00 pm

Location: Blocker 220


Also online via Zoom:
Meeting ID: 998 4499 3279
Password: 724615

Speaker: Fernando Luco, Ph.D., Associate Professor at Department of Economics, Texas A&M University

Faculty Host: Yu Ding, TAMIDS/ESEN

Abstract: Most mobile apps have started tracking consumers’ location and movement patterns in recent years. This type of tracking can allow firms to predict consumers’ future behaviors better and send targeted communications. However, such tracking also raises privacy concerns among app users and regulators. This results in potential trade-offs between the value of granular tracking and privacy concerns. This paper examines three related questions. First, we examine whether granular tracking data add value when predicting consumers’ retail visits relative to traditional metrics. Second, we examine whether the granularity (e.g., frequency) with which these data are tracked impacts the accuracy with which we can predict future retail visits. Finally, we examine if there is heterogeneity in the value of granularity by firm type. Our results show that the accuracy of prediction algorithms improves by 21% with granular tracking data relative to models that use only demographic and behavioral information on past visits. However, when tracking data are collected at longer intervals, the performance of machine learning algorithms decreases, though they still outperform models that use only information on demographics and past behavior. We also find that a deep learning transformer model that uses the entire sequence of latitude-longitude coordinate pairs as input outperforms the ML models by 19% in accuracy but is more computationally expensive. Our models perform significantly better with more (vs. less) granular data for non-chain rather than chain restaurants. Finally, we show how our model may be used to evaluate targeting policies. This is a joint work with Unnati Narang at UIUC.

Biography: Dr. Fernando Luco is Associate Professor of Economics at Texas A&M University. Dr. Luco teaches graduate and undergraduate courses in Industrial Organization and Antitrust. In his courses, he teaches both methodological approaches to examine competitive and strategic firm conduct, as well as tools to quantify the impact of government policies on market outcomes. Dr. Luco’s research focuses on topics in Industrial Organization and Antitrust. His research has been funded by the National Science Foundation, and it has been published in leading economic journals such as the American Economic Review and American Economic Journal: Microeconomics. Dr. Luo received his Ph.D. in Economics from Northwestern University in 2014.

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