Apenas uma postagem? Previsões de vendas diárias de empresas varejistas de beleza e cosmético a partir da influência de mídias sociais

Gabriel Gomes Pessanha; Eduardo Almeida Soares

doi:10.5585/remark.v20i4.17914

Autores

Gabriel Gomes Pessanha Universidade Federal de Alfenas (UNIFAL) – Instituto de Ciências Sociais Aplicadas (ICSA) https://orcid.org/0000-0002-6480-357X
Eduardo Almeida Soares Universidade de Lancaster https://orcid.org/0000-0002-2634-8270

DOI:

https://doi.org/10.5585/remark.v20i4.17914

Palavras-chave:

Mídias sociais, Imagens, Inteligência artificial, Previsão de vendas, Marketing digital, Influenciador digital

Resumo

Objetivo: Estudar a relevância das postagens no Instagram na construção de modelos de previsão de variação de receitas de vendas diárias para empresas varejistas do setor de beleza e cosméticos.

Metodologia: Foram consideradas séries temporais de vendas diárias entre os anos de 2017 e 2019 de 10 empresas varejistas do setor de beleza e cosméticos. Métodos baseados em aprendizagem de máquina foram empregados e os modelos de previsões foram incrementados com variáveis numéricas do perfil oficial da empresa, da postagem feita pelo influenciador digital contratado e as características das imagens postadas pelo influenciador digital foram incluídas nos modelos.

Relevância e Originalidade: O estudo é inovador, pois ultrapassa as reflexões qualitativas sobre a temática e traz evidências empíricas quanto aos impactos na acurácia da previsão a partir da inclusão de variáveis de mídias sociais. Apresentou-se uma estratégia de fusão de dados (numéricos e imagens) para a previsão de vendas diárias de empresas de varejo do setor de beleza e cosméticos.

Principais resultados: Os modelos se mostraram eficientes na previsão e a importância das variáveis likes e engajamento reforça a ideia de que a identificação e referência social gerada pelo ID são importantes aspectos no processo de decisão de compra. Constatou-se que as imagens são responsáveis por adicionar atributos exclusivos que ajudam na previsão e no entendimento dos padrões das séries de vendas.

Contribuições teóricas e metodológicas: O estudo demonstrou, de modo promissor, a eficiência dos métodos baseados em aprendizagem de máquina na previsão de vendas a partir de dados do Instagram, especialmente, no que se refere à incorporação e extração de dados de imagens.

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Biografia do Autor

Gabriel Gomes Pessanha, Universidade Federal de Alfenas (UNIFAL) – Instituto de Ciências Sociais Aplicadas (ICSA)

Doutor em Adminsitração

Eduardo Almeida Soares, Universidade de Lancaster

Mestre

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