Market segmentation: Machine Learning in Marketing in the Context of COVID-19

Authors

DOI:

https://doi.org/10.15381/idata.v26i1.23623

Keywords:

market research, segmentation, artificial intelligence, COVID-19

Abstract

The COVID-19 health crisis has led to unprecedented changes in consumer behavior, as consumers now purchase differently and use different means. Consumers are checking and judging products via electronic devices, shaping trends in consumer segments. This research study aimed to use the clustering model with Machine Learning resources in the analysis of clusters as a resource for consumer segmentation, a major component in business marketing management. A 6-question questionnaire was administered to 506 people ranging from 18 to 65 years old to gauge their opinions about going shopping. A dataset was organized using the data collected and processed using RapidMiner Studio 9.10 software. The optimal number of clusters and their components were obtained from the performance indicator provided by Machine Learning.

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Author Biography

  • Pedro Pablo Chambi Condori, Universidad Nacional Jorge Basadre Grohmann de Tacna. Tacna, Peru

    PhD. Associate professor at the School of Commercial Engineering of Universidad Nacional Jorge Basadre Grohmann de Tacna (Tacna, Peru).

Published

2023-07-31 — Updated on 2023-10-18

Issue

Section

Sistemas e Informática

How to Cite

Market segmentation: Machine Learning in Marketing in the Context of COVID-19. (2023). Industrial Data, 26(1), 275-301. https://doi.org/10.15381/idata.v26i1.23623