Optimising sustainable digital branding through big data: an analysis of the real estate sector across six continents

This research investigates effective strategies for optimising corporate digital brand name and reducing digital marketing costs in the real estate industry by leveraging consumer behavioural data from social media and websites, alongside technical performance metrics. Data were collected over 18 months from 10 globally leading real estate companies operating across six continents, using advanced web and social media analytics tools. The first phase of the study focused on extracting behavioural big data and technical metrics, which were subjected to correlation and regression analyses. In the second phase, an agent-based model (ABM) was developed to simulate consumer behaviour and predict digital brand performance and cost savings. Key findings underscore the synergistic potential of integrating social media and search engine advertisements to enhance brand visibility and surpass competitors. Additionally, reducing organic and paid traffic costs requires optimising website design with concise, user-focused content on landing pages to ensure faster response times. This studys predictive framework bridges the gap between big data analytics and sustainable branding, offering actionable insights for real estate practitioners to align their strategies with evolving consumer demands and environmental goals.