Cabral, Marco Antônio LeandroAbreu, Rafael Bezerra de2025-01-132025-01-132024-09-30ABREU, Rafael Bezerra de. Aplicação do data mining como ferramenta de inovação para decisões estratégicas em vendas em uma empresa de acessórios para moda. Orientador: Dr. Marco Antônio Leandro Cabral. 2024. 63f. Dissertação (Mestrado Profissional em Ciência, Tecnologia e Inovação) - Escola de Ciências e Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2024.https://repositorio.ufrn.br/handle/123456789/61166The advent of Big Data has catalyzed a fundamental shift in companies, requiring the enhancement of their ability to explore data. This evolution is essential for obtaining valuable insights about customers and for effectively leveraging analysis in strategic decision-making. Based on information obtained through innovation tools such as Data Mining, which handles the process of data mining, companies can create strategic actions aimed at achieving predefined goals and objectives. The research is justified by the challenges companies face in data management and the limitations in information handling. In this context, the Data Mining process emerges as a viable alternative for organizational management. The study's objective is to develop a process for applying Data Mining as an innovation tool for strategic sales decisions in a fashion accessories company. The central research question is: How can Data Mining be used to support a company's decision-making process? To address this question, a literature review was conducted, followed by a case study in a company from the sector. The research employed the K-Means algorithm to perform clustering of sales representatives, enabling segmentation into homogeneous groups based on variables such as revenue, order volume, and profit margin. The results demonstrate that using Data Mining, combined with clustering, enabled a detailed analysis of the representatives’ profiles, facilitating the formulation of tailored strategies for each group. For cluster 1, it was recommended to maintain performance through retention and incentive strategies. cluster 0, on the other hand, was identified as the target for corrective actions, including developing new training programs and reviewing commercial policies. Meanwhile, cluster 2 presented opportunities to increase sales volume and profit margins, particularly by adopting cross-selling and up-selling strategies. It is concluded that applying Data Mining brought substantial gains to the company, optimizing processes and enabling more assertive strategic decisions. The final recommendations suggest replicating the process in other areas of the organization and in varied organizational contexts to expand positive outcomes.Acesso AbertoData MiningClusterizaçãoAções estratégicasVendasmasterThesisCNPQ::OUTROS::CIENCIAS