Ferramentas de Digital Analytics e seu poder de previsão sobre o desempenho: uma análise do mercado automobilístico brasileiro

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dc.citation.issue2pt_BR
dc.citation.volume15pt_BR
dc.contributor.authorKimura, Roger Kenji [UNIFESP]
dc.contributor.authorContreras Pinochet, Luis Hernan [UNIFESP]
dc.contributor.authorAzevedo, Marcia Carvalho de [UNIFESP]
dc.coverage.spatialSão Paulopt_BR
dc.date.accessioned2020-07-22T14:08:03Z
dc.date.available2020-07-22T14:08:03Z
dc.date.issued2016
dc.description.abstractThe objective of this paper is to understand how these companies are being mapped and analyzed in relation to sales, with the support of Digital Analytics tools. It was selected the top 10 automotive companies present in Brazil with the highest sales and data were collected on their pages through Digital Analytics tools during two months. It was chosen the multivariate technique of multiple linear regressions by analyzing the relation between the independent variables (collected attributes) with the dependent variable (sales). As a result, it was found that some tools have a better set of parameters that explains the sales of automakers. From the seven Digital Analytics software's observed, six-showed significance in explanatory power. This research was purely quantitative, in which the independent variables that were significant for this study could be grouped into: "Social Media" and "Not Social Media", overcoming a greater concentration of variables "Not Social Media".pt
dc.description.abstractThe objective of this paper is to understand how these companies are being mapped and analyzed in relation to sales, with the support of Digital Analytics tools. It was selected the top 10 automotive companies present in Brazil with the highest sales and data were collected on their pages through Digital Analytics tools during two months. It was chosen the multivariate technique of multiple linear regressions by analyzing the relation between the independent variables (collected attributes) with the dependent variable (sales). As a result, it was found that some tools have a better set of parameters that explains the sales of automakers. From the seven Digital Analytics software's observed, six-showed significance in explanatory power. This research was purely quantitative, in which the independent variables that were significant for this study could be grouped into: "Social Media" and "Not Social Media", overcoming a greater concentration of variables "Not Social Media".en
dc.description.affiliationUniversidade Federal de São Paulo – Unifesp, Brasil
dc.description.affiliationUnifespUniversidade Federal de São Paulo – Unifesp, Brasil
dc.format.extent220-236pt_BR
dc.identifierhttps://doi.org/10.5585/remark.v15i2.3216pt_BR
dc.identifier.citationRevista Brasileira De Marketing. Sao Paulo, v. 15, n. 2, p. 220-236, 2016.pt_BR
dc.identifier.doi10.5585/remark.v15i2.3216pt_BR
dc.identifier.issn2177-5184pt_BR
dc.identifier.urihttps://repositorio.unifesp.br/handle/11600/56199
dc.languageporpt_BR
dc.publisherUniversidade Nove de Julhopt_BR
dc.relation.ispartofRevista Brasileira De Marketingpt_BR
dc.rightsinfo:eu-repo/semantics/openAccesspt_BR
dc.subjectAutomotive Marketpt_BR
dc.subjectPositioning Strategypt_BR
dc.subjectDigital Analyticspt_BR
dc.subjectMercado Automobilísticopt_BR
dc.subjectEstratégia de Posicionamentopt_BR
dc.subjectDigital Analyticspt_BR
dc.titleFerramentas de Digital Analytics e seu poder de previsão sobre o desempenho: uma análise do mercado automobilístico brasileiropt_BR
dc.title.alternativeDigital Analytics tools and their predictive power on performance: an analysis of the brazilian auto marketpt_BR
dc.typeinfo:eu-repo/semantics/articlept_BR
unifesp.campusEscola Paulista de Política, Economia e Negócios (EPPEN)pt_BR
unifesp.departamentoAdministraçãopt_BR
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