The Source of Truth for Places Data

Organizations trust SafeGraph data to drive their business forward. Access the most accurate point of interest (POI) and foot traffic data on the market.


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SafeGraph Points-of-Interest Logo
Core Places
Over 6,400,000 point-of-interest locations where consumers spend time or money.

View the data schema.
SafeGraph Patterns Store Insights Logo
Building footprints with spatial hierarchy for all POIs in the Core dataset.

View the data schema.
SafeGraph POI Data Matching Logo
Foot-traffic insights for places derived from anonymized mobile devices.

View the data schema.

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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. 
Attributes attached to a Place (POI)
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.

Visit the Places technical manual to learn more. 
Polygons (building footprints) represent spatial hierarchy of places.
"Building A Retail Space on top of SafeGraph Places data is fundamental to our platform’s ability to deliver best-in-class insights to commercial real estate brokers"
Scott Bagby
"SafeGraphPlaces help us more accurately create location-based audiences -- the result of this is more efficient ad spend for our clients."
Yoram Greener
Executive Director, JubaPlus (Media Storm's Data Science Group)
"SafeGraph data is at the core of our data pipeline and plays an integral role in completing the customer journey from exposure to in-store visit, transforming OOH into a performance-based media."
Nicholas Wooten
"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."
Shawn Carver
"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 

Data Ingestion logo
We onboard data from thousands of diverse sources. We compare, de-dupe, cross-reference, and discard bad data.
Polygon Drawing Logo
Our building footprints are derived from satellite imagery and supplemented with hand-drawn polygons.
POI Data Merging Logo
We use machine learning and human feedback to associate POI business listing info with building footprints.
Machine Learning Classification Logo
We algorithmically classify brands and denote spatial hierarchy. POIs (like restaurants) can exist within other POIs (like airports).
Benchmark Data Against Truthsets Logo
We leverage unique truth sets to continually improve the accuracy of our datasets.
Data Updated Monthly Logo
Data is updated monthly to account for store openings and closings.

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