The Source of Truth for Places Data To Fuel Innovation & Growth
World class organizations trust SafeGraph data to drive their business forward. Access the most accurate and widely adopted point-of-interest (POI) dataset of business listings and store visitor insights.
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The Most Accurate Point-of-Interest and Store Location Geofences for the U.S.
All of the signal, none of the noise
High Quality POI Data
Our customers trust SafeGraph data to be clean and free of unnecessary noise. Our algorithms work over-time to remove and filter out irrelevant POIs and errors in the data. Better data means better decisions for your business. Visit our point-of-interest guide and FAQ to learn more.
detailed & accurate geometry
Precise Building Footprints
SafeGraph's geofences offer the most precise understanding in the market on where stores are located. Building footprints are derived from satellite imagery and places are spatially hierarchical. Polygons for sub-stores are specified and tied to their parent store Geometry - ex: a Starbucks inside a strip mall.
"Since forecasting models are based on historical trends and data, they quickly became irrelevant when COVID-19 hit. We turned to SafeGraph Patterns foot traffic data to feed our models with an alternative data source representing demand signals that could radically improve downstream visibility and build greater trust with customers around our forecasting models."
"We evaluated several sources of places data for the United States and found the SafeGraph data to be the best overall fit for Esri's requirements, given its relative currency, completeness, and accuracy."
“We evaluated several sources of places data for the United States and found the SafeGraph data to be the best overall fit for Esri's requirements, given its relative currency, completeness, and accuracy.”
Deane Kensok ArcGIS Content CTO
How We Create Our POI Database
We onboard data from thousands of diverse sources. We compare, de-dupe, cross-reference, and discard bad data.
Our building footprints are derived from satellite imagery and supplemented with hand-drawn polygons.
We use machine learning and human feedback to associate POI business listing info with building footprints.
We algorithmically classify brands and denote spatial hierarchy. POIs (like restaurants) can exist within other POIs (like airports).
We leverage unique truth sets to continually improve the accuracy of our datasets.
Data is updated monthly to account for store openings and closings.
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OUR mission IS TO DEMOCRATIZE ACCESS TO DATA FOR EVERYONE
We strive to be the most trusted source to get data on a physical place and make it accessible for all. We're exclusively focused on being a data company with the best quality, coverage, and trust from our partners.
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