Yewon Kim
Assistant Professor of Marketing, Stanford Graduate School of Business
yewonkim[at]stanford.edu
Assistant Professor of Marketing, Stanford Graduate School of Business
yewonkim[at]stanford.edu
I am an Assistant Professor of Marketing at the Stanford Graduate School of Business. My research explores social challenges at the intersection of sustainability and developing economies, focusing on the drivers of sustainable consumption and production through large-scale empirical data and field experiments.
I am also broadly interested in how information frictions shape consumer and firm behavior across various markets and in identifying effective interventions to mitigate these frictions, particularly for market newcomers. With a background in Art History, I find the arts industry a fascinating and valuable research setting; its unique market structure and the experiential nature of its products (e.g., classical music concerts, art exhibitions) provide rich opportunities to study consumer preferences and the role of information in decision-making.
This paper studies strategic consumer shopping behavior in response to a macroeconomic policy in the case of currency reform, and quantifies its unintended consequences for retailers vis-a-vis the policy goal. Using transaction-level data from a large retail chain in India, we document consumer strategies that leverage the presence of retailers to avoid costs associated with the country's currency reform policy. We observe both an increase in returns of cash-purchased items that were bought before demonetization (strategic returns) and a spike in final (unreturned) cash purchases with soon-to-be-illegal notes (strategic purchases). Both practices serve consumer incentives either to receive legal notes from the retailer or to avoid depositing cash in formal bank accounts. Our analysis suggests that strategic consumers benefited the retail chain overall while partly hindering the intended effect of the policy, leaving more than 20 million INR (0.3 million USD) of demonetized notes outside the formal tax network through this retail chain only; when we scale up the estimates to the country's market size, the estimated total impact is at least 100 billion INR (1.5 billion USD). Our findings (i) offer implications for policy makers by quantifying a wide spillover effect of government interventions that goes beyond the target group, and (ii) document a new role of the retail industry - of absorbing, and facilitating a response to, macro shocks.
- Presented at 2025 Workshop in Management Science, 2025 Marketing Dynamics Conference, 2025 Bay Area Marketing Symposium
We examine when, why, and which online ad content drives customer acquisition through the lens of search and learning theory. With a semiconductor firm, we conducted a field experiment that varied ad headlines across eight markets (four products $\times$ two regions) and two sequential placements (display ads and landing page ads). Drawing on search theory, headlines emphasized vertical quality, the likelihood of finding a horizontal match, or transactional ease. To assess the role of prior knowledge, we use features of pre-experiment organic traffic as proxies of prior information. We find strong interaction effects between ad content and prior information on both click-through and conversion rates: Content emphasizing vertical quality and match likelihood outperformed transactional ease content in low-information markets, while the reverse held in high-information markets. Not accounting for this information heterogeneity leads to the misleading conclusion that ad content has no effect. Among the ad types, match-likelihood content had the highest average effect on conversion with the greatest sensitivity to prior knowledge, suggesting that uncertainty about finding a match is a major barrier to engagement. Our findings show that even coarse market-level tailoring of ad content based on inferred priors can significantly improve customer acquisition.
- Presented at 2019 Stanford Marketing seminar, 2019 NYU Marketing seminar, 2019 Columbia Marketing seminar, 2019 Minnesota Marketing seminar, 2019 UT Dallas Marketing seminar, 2021 Yale Marketing seminar, 2021 KAIST Marketing seminar, 2021 QME Conference, 2022 Emory Marketing seminar, 2022 Berkeley Marketing seminar, 2022 Northwestern Marketing Seminar
Firms often see customers churning quickly after limited product experiences. This paper examines whether such early churn is solely driven by customers' low preferences for a given firm or influenced by incomplete information about available products. Using ticket purchase data from a major U.S. symphony center, I find that concert choices exhibit within-customer changes over time that align with predictions under consumer learning. These patterns suggest that 1) first-time customers have incomplete information about concerts and 2) the choices of experienced customers reflect a concert's true average consumption utility ("concert value"). Reduced-form analyses show that the estimated concert values inferred from experienced customers' choices are not correlated with first-timers' initial concert choices but are strongly correlated with their subsequent churn, indicating that an initial visit made under imperfect information shapes a customer's expectations about future concerts. Counterfactual analyses using a structural model highlight the challenge of regaining customers after an initial low-value experience, emphasizing the importance of pre-visit interventions (e.g., introductory marketing, assortment design for first-time customers) in reducing early churn.
We study complementarities between brands in the context of collaborations across museums. Over the course of our sample, one major museum with a highly recognized brand closed temporarily and sequentially collaborated with two established local museums. With individual panel data on museum memberships around these events, we measure how collaborations affect demand using an empirical framework of complementarities that are newly applied to the branding context. We observe two counter-acting demand patterns. First, customers with no history of buying membership from either museum enter the market, suggesting brand complementarities. Second, a sub-group of customers who previously purchased from either or both of the museums display decreased demand, consistent with brand dilution. Any structural approach that models the demand for collaboration with existing preferences for separate brands fails to create accurate demand predictions. The magnitude of the offsetting forces varies between collaboration events, which makes demand prediction even more challenging. These results call for a theory of brand being beyond a fixed utility primitive and have implications for counterfactuals that involve combining or altering of brands.
- Presented at 2024 China-India Insights Conference (plenary session) and 2024 INFORMS Annual Meeting
- Funded by Asian Development Bank ($77,000 grant) and Stanford BGS Research Grant ($20,000)
- Field experiment completed in June 2025
- On-campus field experiment completed in June 2025
- In collaboration with Stanford Food Institute and Residential & Dining Enterprises