Market segmentation: Machine Learning in Marketing in the Context of COVID-19
Descripción del Articulo
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 mo...
Autor: | |
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Formato: | artículo |
Fecha de Publicación: | 2023 |
Institución: | Universidad Nacional Mayor de San Marcos |
Repositorio: | Revistas - Universidad Nacional Mayor de San Marcos |
Lenguaje: | español inglés |
OAI Identifier: | oai:ojs.csi.unmsm:article/23623 |
Enlace del recurso: | https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/23623 |
Nivel de acceso: | acceso abierto |
Materia: | market research segmentation artificial intelligence COVID-19 investigación de mercados segmentación inteligencia artificial covid-19 |
Sumario: | 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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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).