GSDSI (Global Source Data Solutions Inc.) equips commercial real estate investors, REITs, and developers with 155M U.S. property records (residential + commercial) layered against 700M+ device foot-traffic signals and 26M+ U.S. POIs — giving site selection, portfolio benchmarking, and tenant analytics teams the behavioral ground truth that drive-time models and broker opinions cannot provide. Commercial real estate decisions involve significant capital commitments that depend on accurate assessments of location quality, consumer demand, and competitive dynamics. Traditional site selection methods like drive-time analysis, demographic overlays, and broker opinions provide useful context but fail to capture the behavioral reality of how consumers actually move through and interact with commercial locations. GSDSI transforms real estate analytics by providing device-level foot traffic data from 700M+ devices, so property investors and developers can evaluate sites based on actual visitation patterns rather than modeled estimates. Portfolio managers benchmark property performance across their holdings using normalized visit metrics (visits per square foot, average dwell time, repeat visitation rate), identifying underperformers and diagnosing whether declines stem from market shifts, tenant mix issues, or competitive encroachment. Site selection teams analyze visitor origin data to define true trade areas, assess co-tenancy effects between anchor tenants and inline retailers, and find whitespace markets where consumer demand exists but commercial supply is limited.
GSDSI's data catalog is used across this vertical for procurement, activation, measurement, and risk scenarios that require identity-resolved, privacy-safe signals at scale. The combinations vary by use case — adtech programs lean on identity graph plus CTV/ACR plus clickstream; insurance programs lean on property data plus consumer signals; real-estate programs lean on property plus mobility plus POI — but the evaluation pattern is consistent: scoped sample, match-rate audit, privacy-envelope review, and production sign-off against documented SLAs.