Abstract
The COVID-19 pandemic has significantly disrupted the global economy at an unprecedented scale since its start in early 2020. Furthermore, it is estimated that a third of the workforce in the U.S. changed to work from home (Brynjolfsson et al. 2020). As consumers are spending more time at home, data shows that panic buying changed demand for items such as hand sanitizer and toilet paper. The increase for certain categories in consumer spending during the pandemic has been accompanied by a spike in the utilization of e-commerce channels. COVID-19 accelerated consumers move to purchasing goods online versus traditional physical stores by five years (Perez 2020). According to the U.S. Census Bureau, consumers increased their e-commerce spending to $211.5 billion during the second quarter, an increase of 31.8% quarter over quarter (Palmer 2020). The sudden nature of the changes related to COVID-19 purchase behavior makes it harder for marketers to respond effectively.
As research on the topic of COVID-19 is starting to appear in the literature, there is not enough work in the area of consumer purchase behavior. In this paper, we utilize three real-time datasets to understand customer dynamics from March 2020 to December 2020 during the pandemic. Combining these data sources allows us to enhance our understanding of the general purchasing behavior at city level during the pandemic. We identify product categories that were the primary drivers of a sharp increase (decrease) in spending and the extent to which this increase (decrease) was maintained over time. We also shed light on stressors such as the number of COVID-19 cases and death by city and their impact on time spent at home and retail stores. By doing so, we contribute to the literature on panic buying which is still not well understood in the literature (Barnes et al. 2020).