Selling Choice
Close a Store to Open a Pandora's Box? The Effects of Store Closure on Sales, Omnichannel Shopping, and Mobile App Usage
Taotao Ye & Venkatesh (Venky) Shankar
Marketing Science, forthcoming
Abstract:
What are the causal effects of the closure of a store on a retail chain's overall, offline, and online sales? We address this central research question using sales, shopper transaction, and mobile app usage data from a large retail chain that closed 34 stores across states in a month. We use the difference-in-differences approach, creating propensity score-matched control counties and controlling for selection. We examine potential moderators of these effects and underlying mechanisms using individual shopper-level and mobile app user-level data, including analyzing app engagement through topic modeling. Our findings reveal that closing a store opens a Pandora's box in that it triggers significant net monthly sales loss of $209,317 (more than the average monthly sales of the closed store), representing 18.7% of the retailer's net sales in the county with the closed store because of spillover effects on other channel purchases by the retailer's customers in that county. The numbers of the retailer's active customers, new customers, active app users, new app users, and their mobile app engagement all decline postclosure. Store closure has a negative spillover effect on even nearby shoppers who never shopped at the closed store. Loyal shoppers among nonvisitors to the closed store and app users are more tolerant of store closure than other shoppers. To mitigate adverse effects, retail chains can strategically choose stores closer to other stores in the chain, with a high percentage of in-store discounts and online sales, and a low value of product returns to close. Additionally, they can redirect shoppers in affected counties to the chain's nearby stores and online (in particular, the mobile app) by offering discounts and promoting store and product information in the app.
Behavioral Skimming: Theory and Evidence from Resale Markets
Andreas Kraft & Raghunath Rao
University of Chicago Working Paper, October 2024
Abstract:
A large body of research shows that even when information is accessible, consumers often fail to attend to it. To what extent and under what conditions can firms profit from such consumer inattention? We study this question theoretically and empirically in the used car market, focusing on the widely documented left-digit bias. Theoretically, firms can profit from targeting the most inattentive consumers. Leveraging a detailed dataset of millions of automobile transactions from a seven-year period, we find that consumers exhibit inattention in the form of left-digit bias to the odometer, and such inattention is estimated to be significantly more for consumers who buy from firms. Compared to private sellers, car dealerships transact with ex-post significantly more left-digit biased consumers. Dealerships sell more vehicles whose odometers are below round numbers, sell them faster, and extract higher margins from these vehicles. Our results imply that intermediaries can "skim" consumers with specific behavioral biases and extract surplus from selling to them.
To Dispose or Eat? The Impact of Perceived Healthiness on Consumption Decisions for About-to-Expire Foods
Jeehye Christine Kim, Young Eun Huh & Brent McFerran
Journal of Marketing, forthcoming
Abstract:
Perceived healthiness of food is generally regarded as a positive attribute in food choices as it positively impacts consumers' preferences. The current research demonstrates that in contexts where there is a time delay between a food's production and its consumption (referred to as "about-to-expire" food), strong perceptions of a food's healthiness can be detrimental. This is because consumers hold a lay theory that healthy food expires more quickly. In eight studies (N = 3,552), we find that merely portraying food as healthy increases the perception that it expires quickly and that this effect attenuates when consumers hold the lay theory weakly or have a high level of knowledge about food expiration. Importantly, this lay theory leads consumers to avoid consuming healthy (vs. non-healthy) about-to-expire food, resulting in increased disposal intentions and decreased preferences. In designing sales promotions for about-to-expire food, managers should consider the healthiness of food products, as consumers prefer different types of sales promotions and require different magnitudes of price discounts for healthy (vs. non-healthy) about-to-expire food. Finally, adding an expiration date label that provides unambiguous guidance (i.e., "consume by") can effectively mitigate the detrimental effect of perceived healthiness on the consumption for about-to-expire food.
Choice Frictions in Large Assortments
Olivia Natan
Marketing Science, forthcoming
Abstract:
This paper studies how the growth and evolution of product assortments impact consumer adoption, churn, and purchase frequency. Most economic theories of product variety and the value of platforms suggest consumers at least weakly prefer larger product assortments. In contrast, the psychological literature on the phenomenon of choice overload finds that larger assortments overwhelm consumers with decision costs or induce more regret. I provide empirical evidence of how the size and contents of product assortments impact consumers across their lifetime on an online food delivery platform. I find that assortment expansion increases the acquisition of new consumers but reduces the frequency of consumption among consumers who remain on the platform. I rationalize these effects on returning customers via a model of costly attention and choice under limited information. Counterfactual exercises show that targeting choice set reductions can improve revenue among existing customers.
From Novelty to Norm: Uncovering the Drivers of Virtual Tour Effectiveness in Real Estate Sales
Miremad Soleymanian & Yi Qian
NBER Working Paper, November 2024
Abstract:
This study examines the effectiveness of virtual tours and digital marketing strategies in enhancing real estate sales using a unique dataset combining MLS data, government-assessed property values, and agents' marketing activities. While virtual tours are often perceived as a powerful tool to boost sales, their impact is context-dependent. Using classical econometric models and causal machine learning techniques, we find that virtual tours increase property sale prices by an average of 1%. However, the effect has declined over time, particularly post-COVID, indicating a shift from being a novel feature to a standard practice. Further analysis using causal random forests reveals significant heterogeneity in their effectiveness across property attributes, market conditions, and agent characteristics. Virtual tours are less impactful for highly differentiated properties but more beneficial in competitive markets and for less experienced agents who lack familiarity with the local market. These results suggest that real estate agents may benefit from considering property features, market dynamics, and their own experience when deciding how to use virtual tours. Our findings offer valuable insights for practitioners looking to optimize digital marketing strategies and enhance sales performance.