Shopping Missions in Online Grocery Shopping

Abstract

This study introduces a novel mission-based model for segmenting consumers in the online grocery market, leveraging extensive transaction data from a leading U.S. supermarket chain. Utilizing BERTopic modeling, we analyze shopping basket compositions to identify distinct consumer shopping missions. Our methodology uncovers fifteen unique missions, each reflecting specific consumer preferences and behaviors. These range from "Versatile Kitchen Staples" to "Health and Self-Care," highlighting diverse shopping strategies. The findings reveal dynamic shifts in consumer behavior during the COVID-19 pandemic and suggest targeted marketing strategies that can enhance customer engagement.

Keywords: Online Grocery Shopping, Consumer Behavior, Market Segmentation, Data Analytics, Machine Learning, COVID-19 Pandemic, Shopping Missions, BERTopic Modeling

JEL Classification: M31