Desenvolvimento de uma plataforma de inteligência para o setor imobiliário

Abstract

This study aimed to develop an intelligence platform for the real estate sector, with the aim of optimizing the connection between supply and demand for properties and exploring market trends for investor decision-making. The methodology consisted of creating the platform and validating it using a sample of data from the real estate market in Belo Horizonte, MG. The platform's cyclical operating dynamics ensured that, regardless of the order between listing and searching for a property, information was not lost. The simulations carried out demonstrated that the platform can significantly increase efficiency for both consumers and investors, facilitating real estate transactions and providing immediate feedback to advertisers. Furthermore, a market analysis tool proved useful for identifying types of properties and regions suitable for investment. The analysis highlighted prominent property typologies in the city, prominent regions for a given typology, relationships between supply and demand and trending forms of negotiation. Contributions indicated that the platform can fill gaps in the real estate market, contributing to more informed and efficient decisions. Furthermore, its use by a significant number of users and in different economic and social contexts has allowed a broader and more detailed view of its possibilities.