Data-Driven Decision Making on Amazon: A Methodology for Assessing Product Potential and Competition

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Amazon Marketplace, especially for small and medium -sized enterprises, transforms the ascending move with a selection focused on facts. Although huge research emphasizes the standards for choosing products and market access, the unique and complex technique for evaluating the potential of the produ...

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Autor: Korshun, Artem
Formato: artículo
Fecha de Publicación:2025
Institución:Universidad Nacional de Ingeniería
Repositorio:Revistas - Universidad Nacional de Ingeniería
Lenguaje:español
OAI Identifier:oai:oai:revistas.uni.edu.pe:article/2598
Enlace del recurso:https://revistas.uni.edu.pe/index.php/iecos/article/view/2598
Nivel de acceso:acceso abierto
Materia:Decision-making
Competence
Methodology
Toma de decisiones
Competencia
Metodología
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oai_identifier_str oai:oai:revistas.uni.edu.pe:article/2598
network_acronym_str REVUNI
network_name_str Revistas - Universidad Nacional de Ingeniería
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dc.title.none.fl_str_mv Data-Driven Decision Making on Amazon: A Methodology for Assessing Product Potential and Competition
Toma de decisiones basada en datos en Amazon: Una metodología para evaluar el potencial de los productos y la competencia
title Data-Driven Decision Making on Amazon: A Methodology for Assessing Product Potential and Competition
spellingShingle Data-Driven Decision Making on Amazon: A Methodology for Assessing Product Potential and Competition
Korshun, Artem
Decision-making
Competence
Methodology
Toma de decisiones
Competencia
Metodología
title_short Data-Driven Decision Making on Amazon: A Methodology for Assessing Product Potential and Competition
title_full Data-Driven Decision Making on Amazon: A Methodology for Assessing Product Potential and Competition
title_fullStr Data-Driven Decision Making on Amazon: A Methodology for Assessing Product Potential and Competition
title_full_unstemmed Data-Driven Decision Making on Amazon: A Methodology for Assessing Product Potential and Competition
title_sort Data-Driven Decision Making on Amazon: A Methodology for Assessing Product Potential and Competition
dc.creator.none.fl_str_mv Korshun, Artem
author Korshun, Artem
author_facet Korshun, Artem
author_role author
dc.subject.none.fl_str_mv Decision-making
Competence
Methodology
Toma de decisiones
Competencia
Metodología
topic Decision-making
Competence
Methodology
Toma de decisiones
Competencia
Metodología
description Amazon Marketplace, especially for small and medium -sized enterprises, transforms the ascending move with a selection focused on facts. Although huge research emphasizes the standards for choosing products and market access, the unique and complex technique for evaluating the potential of the product and the opposition remains suspicious. This will look at the bridges of this key hole through the offer of integrative methodology controlled records rooted in assessing the relevance of keywords, assessing the area of interest length and evaluation of competition intensity, explicitly tailored to Amazon sellers. Using a mixed technology method, the frame systematically combines quantitative data from analytical structures (business words, helium 10 and Keepa) and qualitative techniques of market studio. The results show that the accurate evaluation of the relevance of keywords significantly affects the area of visibility and careful estimation of the size of the market effectively alleviates the risks of its own excessively aggressive or decreasing niches. Methodology - Studies accept sophisticated framework of mixed technologies combining evaluation of quantitative records and qualitative reviews, reflecting the top dynamics of Amazon Marketplace. The preliminary phase uses the analysis of the frequency of keywords and a metric of keywords from business words to measure the area of interest as it should be. After the comprehensive evaluation of monetary viability, the integration of margin evaluation and the prognosis of breaking is guaranteed by monetary feasibility. The evaluation of the competition achieved through Keep, identifies the techniques of ancient prices and the longevity of the competition and determines the niches with the sustainable market dynamics. In addition, the Helium 10 is used to monitor the price growth prices and the recognition of unnatural spikes indicating unethical competition. Findings - The implemented technique correctly identifies niches characterized by a strong challenge for, mild competition and favorable financial metrics. The analysis shows that niches with the assessment of keyword relevance in the range of 30% to 60% bring the most effective stability and increase the visibility of the list and the ability to convert. Evaluation of financial viability, fundamentally specializing in margins and stock turnover, further specify the selection, except for goods with thin edges and supersaturation. In particular, observing the symptoms of unethical competition, along with an unnatural accumulation overview and competing monopolization strategies, in particular reduced market access errors.  Conclusion - This will look at the introduction of the robust method of custom -made records for the contributors of Amazon Marketplace, which effectively solves key gaps in product evaluation and competitive evaluation. A systematic combination of a critic of quantitative relevance of keywords, thorough market sizing strategies and a unique evaluation of competition gives you strategic clarity and surgical predictability. The following studies are proposed to include advanced predictive analytical equipment, which improves the accuracy and scalability of the selection.
publishDate 2025
dc.date.none.fl_str_mv 2025-09-30
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer Reviewed
Evaluado por pares
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.uni.edu.pe/index.php/iecos/article/view/2598
10.21754/iecos.v26i2.2598
url https://revistas.uni.edu.pe/index.php/iecos/article/view/2598
identifier_str_mv 10.21754/iecos.v26i2.2598
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv https://revistas.uni.edu.pe/index.php/iecos/article/view/2598/3436
dc.rights.none.fl_str_mv Derechos de autor 2025 Artem Korshun
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2025 Artem Korshun
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidad Nacional de Ingeniería
publisher.none.fl_str_mv Universidad Nacional de Ingeniería
dc.source.none.fl_str_mv revista IECOS; Vol. 26 No. 2 (2025)
Revista IECOS; Vol. 26 Núm. 2 (2025)
2788-7480
2961-2845
10.21754/iecos.v26i2
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spelling Data-Driven Decision Making on Amazon: A Methodology for Assessing Product Potential and CompetitionToma de decisiones basada en datos en Amazon: Una metodología para evaluar el potencial de los productos y la competenciaKorshun, ArtemDecision-makingCompetenceMethodologyToma de decisionesCompetenciaMetodologíaAmazon Marketplace, especially for small and medium -sized enterprises, transforms the ascending move with a selection focused on facts. Although huge research emphasizes the standards for choosing products and market access, the unique and complex technique for evaluating the potential of the product and the opposition remains suspicious. This will look at the bridges of this key hole through the offer of integrative methodology controlled records rooted in assessing the relevance of keywords, assessing the area of interest length and evaluation of competition intensity, explicitly tailored to Amazon sellers. Using a mixed technology method, the frame systematically combines quantitative data from analytical structures (business words, helium 10 and Keepa) and qualitative techniques of market studio. The results show that the accurate evaluation of the relevance of keywords significantly affects the area of visibility and careful estimation of the size of the market effectively alleviates the risks of its own excessively aggressive or decreasing niches. Methodology - Studies accept sophisticated framework of mixed technologies combining evaluation of quantitative records and qualitative reviews, reflecting the top dynamics of Amazon Marketplace. The preliminary phase uses the analysis of the frequency of keywords and a metric of keywords from business words to measure the area of interest as it should be. After the comprehensive evaluation of monetary viability, the integration of margin evaluation and the prognosis of breaking is guaranteed by monetary feasibility. The evaluation of the competition achieved through Keep, identifies the techniques of ancient prices and the longevity of the competition and determines the niches with the sustainable market dynamics. In addition, the Helium 10 is used to monitor the price growth prices and the recognition of unnatural spikes indicating unethical competition. Findings - The implemented technique correctly identifies niches characterized by a strong challenge for, mild competition and favorable financial metrics. The analysis shows that niches with the assessment of keyword relevance in the range of 30% to 60% bring the most effective stability and increase the visibility of the list and the ability to convert. Evaluation of financial viability, fundamentally specializing in margins and stock turnover, further specify the selection, except for goods with thin edges and supersaturation. In particular, observing the symptoms of unethical competition, along with an unnatural accumulation overview and competing monopolization strategies, in particular reduced market access errors.  Conclusion - This will look at the introduction of the robust method of custom -made records for the contributors of Amazon Marketplace, which effectively solves key gaps in product evaluation and competitive evaluation. A systematic combination of a critic of quantitative relevance of keywords, thorough market sizing strategies and a unique evaluation of competition gives you strategic clarity and surgical predictability. The following studies are proposed to include advanced predictive analytical equipment, which improves the accuracy and scalability of the selection.Amazon Marketplace, especialmente para las pequeñas y medianas empresas, transforma el movimiento ascendente con una selección centrada en los hechos. Aunque las investigaciones a gran escala hacen hincapié en los criterios para elegir productos y acceder al mercado, la técnica única y compleja para evaluar el potencial del producto y la oposición sigue siendo sospechosa. Esto analizará los puentes de esta cerradura clave a través de la oferta de registros controlados de metodología integradora basados en la evaluación de la relevancia de las palabras clave, la evaluación de la longitud del área de interés y la evaluación de la intensidad de la competencia, adaptados explícitamente a los vendedores de Amazon. Utilizando un método de tecnología mixta, el marco combina sistemáticamente datos cuantitativos de estructuras analíticas (palabras de negocio, helio 10 y Keepa) y técnicas cualitativas de estudio de mercado. Los resultados muestran que la evaluación precisa de la relevancia de las palabras clave afecta significativamente al área de visibilidad y que una estimación cuidadosa del tamaño del mercado alivia eficazmente los riesgos de sus propios nichos excesivamente agresivos o en declive. Metodología: los estudios aceptan un marco sofisticado de tecnologías mixtas que combinan la evaluación de registros cuantitativos y revisiones cualitativas, reflejando la dinámica superior del mercado de Amazon. La fase preliminar utiliza el análisis de la frecuencia de las palabras clave y una métrica de palabras clave de términos comerciales para medir el área de interés como debe ser. Tras la evaluación exhaustiva de la viabilidad monetaria, la integración de la evaluación del margen y el pronóstico de ruptura queda garantizada por la viabilidad monetaria. La evaluación de la competencia realizada a través de Keep identifica las técnicas de precios antiguos y la longevidad de la competencia, y determina los nichos con dinámicas de mercado sostenibles. Además, se utiliza Helium 10 para supervisar el crecimiento de los precios y el reconocimiento de picos antinaturales que indican una competencia poco ética. Resultados: la técnica implementada identifica correctamente los nichos caracterizados por un fuerte desafío, una competencia moderada y métricas financieras favorables. El análisis muestra que los nichos con una relevancia de palabras clave entre el 30 % y el 60 % aportan la estabilidad más eficaz y aumentan la visibilidad de la lista y la capacidad de conversión. La evaluación de la viabilidad financiera, especializada fundamentalmente en márgenes y rotación de existencias, especifica aún más la selección, excepto en el caso de los productos con márgenes reducidos y sobresaturación. En particular, se observan los síntomas de una competencia poco ética, junto con una acumulación antinatural y estrategias de monopolización competitivas, en particular errores de acceso reducido al mercado. Conclusión: se analizará la introducción de un método sólido de registros personalizados para los colaboradores de Amazon Marketplace, que resuelve de manera eficaz las principales deficiencias en la evaluación de productos y la evaluación competitiva. Una combinación sistemática de un análisis crítico de la relevancia cuantitativa de las palabras clave, estrategias exhaustivas de dimensionamiento del mercado y una evaluación única de la competencia le proporciona claridad estratégica y previsibilidad quirúrgica. Se proponen los siguientes estudios para incluir equipos analíticos predictivos avanzados, que mejoran la precisión y la escalabilidad de la selección.Universidad Nacional de Ingeniería2025-09-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer ReviewedEvaluado por paresapplication/pdfhttps://revistas.uni.edu.pe/index.php/iecos/article/view/259810.21754/iecos.v26i2.2598revista IECOS; Vol. 26 No. 2 (2025)Revista IECOS; Vol. 26 Núm. 2 (2025)2788-74802961-284510.21754/iecos.v26i2reponame:Revistas - Universidad Nacional de Ingenieríainstname:Universidad Nacional de Ingenieríainstacron:UNIspahttps://revistas.uni.edu.pe/index.php/iecos/article/view/2598/3436Derechos de autor 2025 Artem Korshunhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:oai:revistas.uni.edu.pe:article/25982025-09-30T20:39:16Z
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