GSDSI's flagship location product — a comprehensive global Points of Interest database with 26M+ U.S. locations and growing international coverage. Each POI record includes precise polygon boundaries, brand-to-parent hierarchy mapping, NAICS classification codes, centroid coordinates, opening hours, and rich place attributes. Purpose-built for foot traffic measurement, trade area modeling, competitive benchmarking, site selection, and campaign attribution at any geographic scale.
GSDSI's POI database is constructed through a multi-source aggregation pipeline that combines authoritative business registries, commercial data partnerships, satellite and aerial imagery verification, and crowdsourced validation. Each Point of Interest is geocoded with a precise polygon boundary (not just a centroid pin) that reflects the actual physical footprint of the location, enabling accurate visit attribution even in dense commercial environments like shopping malls, strip centers, and mixed-use developments. Brand hierarchy mapping links every franchise, subsidiary, and DBA location to its parent company, supporting rollup analytics from individual store to brand to corporate parent. NAICS classification codes are assigned and verified for every POI, enabling category-level analysis across retail, restaurant, healthcare, financial services, entertainment, and dozens of other verticals. The database is refreshed daily to capture new openings, permanent closures, and attribute changes, with historical snapshots available for longitudinal analysis.
Retailers and QSR brands use POI data for competitive benchmarking, comparing their locations' foot traffic against competitors at the brand, category, and trade area level. Real estate investment firms evaluate acquisition targets by analyzing foot traffic density, visitor origins, and co-tenancy effects at properties anchored by specific POI brands. Media agencies build geofence-based audience segments by defining custom boundaries around retail locations, events, or competitor sites, then targeting devices observed within those geofences with relevant advertising. Site selection teams use the POI database to identify whitespace markets where consumer demand exists but competitive supply is limited, overlaying foot traffic patterns with demographic and mobility data to score potential locations. Attribution platforms match ad-exposed devices against POI geofences to measure whether campaign impressions drove incremental store visits, providing closed-loop measurement from impression to visit.
Location buyers inspect polygons, not just POI counts, using dense malls, strip centers, campuses, and same-address businesses to expose boundary errors.