Smart Construction Management

Applying AI for Enhanced Real Estate Marketing and Consumer Insights

Abstract

The integration of construction management with artificial intelligence (AI) in real estate marketing presents a novel approach to enhance consumer segmentation and trend analysis. This study focuses on the application of Monte Carlo simulations and K-Means clustering to address the absence of direct customer income data and optimize marketing strategies for Summarecon Mutiara Makassar. By leveraging data from the Indonesian Central Bureau of Statistics and customer payment records, we simulate income distributions across 14 sub-districts in Makassar. The Monte Carlo method, grounded in the law of large numbers, generates realistic income scenarios, while K-Means clustering identifies distinct customer segments based on income and payment behaviors. The results reveal three primary customer segments, each with unique spending patterns and financial profiles. This segmentation enables targeted marketing efforts, ensuring tailored strategies for different consumer groups. Additionally, the study emphasizes the role of value engineering in enhancing project value by aligning with customer-valued functions at minimal costs. The findings underscore the importance of comprehensive data analysis and simulation techniques in real estate marketing, providing actionable insights for optimizing marketing strategies and improving customer satisfaction. This research contributes to the growing body of knowledge on AI applications in real estate and underscores the potential of simulation-based approaches in addressing data gaps and enhancing market understanding.