GSDSI (Global Source Data Solutions Inc.) supports healthcare and pharmaceutical buyers with aggregated, de-identified mobility intelligence from 700M+ devices, 26M+ U.S. POIs, and ACR-derived CTV viewership — engineered to reveal population-level patient catchment, provider accessibility, and DTC-campaign attribution without exposing any protected health information (PHI). Healthcare and pharmaceutical organizations face unique data challenges that call for privacy-safe analytical approaches. Patient mobility patterns, provider accessibility, and campaign effectiveness all depend on location intelligence, but the sensitive nature of healthcare data demands rigorous privacy protections. GSDSI addresses this by providing aggregated, de-identified mobility intelligence that reveals how populations interact with healthcare facilities without exposing any protected health information (PHI). Health systems use our foot traffic data to evaluate potential clinic and urgent care locations, analyzing patient catchment areas, competitive provider proximity, and population accessibility gaps in underserved communities. Pharmaceutical companies measure the effectiveness of direct-to-consumer (DTC) advertising campaigns by correlating ad exposure (tracked through CTV viewership and mobile device signals) with subsequent visits to pharmacies, specialist providers, and treatment centers. All measurement is performed at the aggregated level, with no individual patient tracking or health condition inference. Retail pharmacy chains use POI-level competitive benchmarking to compare store performance against competitors, identify high-potential locations for new openings, and optimize drive-through versus in-store service models based on actual patient visitation patterns and dwell time analysis.
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.