Building occupancy patterns strongly influence organizational effectiveness during the operation and maintenance (O&M) phase. Actual occupancy is highly variable over time and differs from the static occupancy levels considered during design phases. Consequently, poor levels of space management, use, and cleanness are detected during the O&M phase, affecting user well-being and satisfaction. Occupancy monitoring and analysis are needed to achieve effective and efficient facility management (FM) and user well-being. The article explores the scientific domains of occupancy detection and analysis, and related main approaches, i.e., post-occupancy evaluations (POEs) and digital twins (DTs) in the architecture, engineering, construction and operation (AECO) industry. A scientometric approach through science mapping and data visualization is applied to analyze 386 bibliographic records from Scopus database. The temporal trend analysis and conceptual structure of the scientific domain are investigated, drawing a picture of the body of knowledge. The performed analysis uncovered the temporal distribution of the publications and the relationships among the topics. DT is a recent topic in the early stages of investigation, while POEs are mature approaches related to sustainability, energy efficiency, productivity, building performance optimization, and user satisfaction. Occupancy detection and analysis are related to FM but less investigated topics in recent years. The research aims to uncover possible research gaps and open challenges in the field for further research aiming to support the optimization of occupancy and space management in the O&M phase, increasing workplace adaptability to changing conditions and needs and user satisfaction and well-being over time.