Weather sensitivity analysis on grocery shopping

Abstract

Although weather is known to impact consumer behavior and, accordingly, businesses react to weather-influenced consumer behavior, marketing scholars have not examined weather marketing as intensively as its practical importance suggests. To fill this research void, we choose the grocery shopping setting, where weather influences shoppers’ shopping trip incidence and basket size. We theorize that the weather event (i.e., rain, snow, thunder, and fog) decreases both the shopping trip and the basket size. On the shopping trip, however, the negative weather impact is mitigated for less frequent shoppers because such shoppers have a higher basic shopping need than more frequent shoppers. Similarly, in terms of the basket size, store familiarity lessens such a negative weather impact because shoppers in a familiar environment are more comfortable about unfavorable weather. Besides, when sustained bad weather is expected, shoppers may turn proactive in determining when to go shopping. Our empirical application combines rich scanner panel data and daily weather data to explain both shopping trip and basket size simultaneously in the form of a Type 2 Tobit model. Our analysis results support our weather marketing hypotheses.