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Shopping missions in online grocery shopping

Authors: Pocsay, Marc Enrico; Han, Qiwei; Kaiser, Maximilian;

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.

Country
Portugal
Related Organizations
Keywords

Market segmentation, Data analytics, Covid-19 Pandemic, Machine learning, Shopping missions, Online grocery shopping, BERTopic Modeling, SDG 12 - Responsible Consumption and Production, Consumer behavior

  • BIP!
    Impact byBIP!
    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green