Segmentação de Clientes e Otimização de Estratégias: Abordagens Avançadas com Analise RFM e Algoritmos de Clusterização

Abstract

This article discusses customer segmentation and strategy optimiza tion through RFM analysis and clustering algorithms. RFM analysis (Recency, Frequency, and Monetary Value) identifies high-value customers, helping prio ritize marketing efforts for retention and loyalty. The study’s motivation is the need for companies to better understand their customers, improve their marke ting strategies, and boost business growth. Combining RFM analysis with data mining techniques provides valuable insights for customer relationship mana gement and business operations optimization. The study applies RFM analysis using the k-Means method to evaluate its effectiveness, enabling the creation of distinct customer allocation profiles, providing important information for in vestment management and optimization, demonstrating to be an effective appro ach for customer segmentation in financial contexts and for strategic decision making in the market.