A global mobility dataset capturing device-level movement and visitation patterns from consented app, Wi-Fi, and SDK sources. Includes real-time and historical location events designed for foot traffic measurement, movement analysis, dwell time tracking, origin-destination modeling, and cross-border travel intelligence across 150+ countries.
Product Answer Summary
Product category: Location & Place Intelligence
What it contains: Lat/long coordinates, Timestamp & dwell time, Aggregated movement flows, Origin-destination matrices, Cross-border travel patterns, Transportation mode signals
Delivery formats: CSV, JSON, Parquet, API
Who uses it: enterprise data buyers evaluating activation, measurement, analytics, enrichment, risk, or research workflows.
Key Features
700M+ global devices
150+ country coverage
Daily data freshness
Historical data back to 2019
Custom geography support
Feed Specifications
Record scale: Daily mobility events, 150+ countries
Coverage: Global (150+ countries)
Refresh cadence: Daily
Delivery formats: Parquet, JSON, S3, SFTP
How Mobility and Location Data Is Sourced
GSDSI collects device-level latitude and longitude signals from over 700 million mobile devices worldwide through a network of SDK-integrated mobile applications, Wi-Fi sources, and consented data partners. Each location observation includes precise GPS coordinates, a timestamp, estimated horizontal accuracy, dwell time calculation, and device type metadata. The data goes through rigorous quality filtering to remove centroid pings, VPN-masked locations, and signals with accuracy radii that exceed acceptable thresholds. Visit attribution algorithms match cleaned location signals against our repository of 26M+ U.S. Points of Interest with polygon boundaries, converting raw GPS pings into structured visit events. For broader mobility analysis, raw signals are also processed into origin-destination flow matrices that quantify how populations move between geographic zones. Transportation mode classification distinguishes between pedestrian, vehicular, rail, and air travel. Cross-border travel detection identifies international movement patterns for tourism and trade corridor monitoring. Historical data goes back to 2019, supporting longitudinal trend analysis and year-over-year comparisons.
Common Applications
Retailers and QSR brands use this data to measure foot traffic trends, benchmark visitation against competitors, and analyze trade areas for site selection. Real estate investment firms evaluate acquisitions by examining foot traffic density, visitor origins, and temporal visitation trends. Tourism boards measure inbound visitor volumes by origin country, track seasonal patterns, and benchmark destination competitiveness. Urban planners use origin-destination matrices to optimize transit routes and model the impact of policy changes on commuter behavior. Financial analysts use location-derived foot traffic as an alternative data input for revenue proxy models, tracking same-store trends at publicly traded companies. Government agencies and public health organizations use aggregated mobility data for transportation planning, pandemic response, and infrastructure investment decisions.
How buyers diligence mobility data
Mobility-data diligence should be geography-specific: observed daily devices, accuracy filtering, sensitive-location exclusions, dwell logic, and consent documentation.
Product-specific diligence checks
Measure usable device density in target geographies.
Review GPS filters, centroid suppression, VPN artifacts, and dwell rules.
Define sensitive-category exclusions and retention limits.
Confirm whether delivery is raw events, visits, or aggregates.