The Proximity dataset scores block groups across 72 behavioral segments. Sources include public geotagged posts from Twitter, Instagram, Facebook, Flickr, Foursquare, Meetup, and more.
Social users
Data points
Block groups
Unique segments
Hip Hop Culture
All About Hair
Body Art
Hipster
Girl Squad
Late-Night Leisure
Dog Lovers
Bookish
Trendy Eats
The Geosocial Proximity dataset is a classification of areas based on what people are doing and saying there. It originates from where the post was tagged. By combining traditional demographics in trade areas with social behaviors in close proximity, retailers and restaurants can reveal hidden location characteristics that drive business success.
Activate the Geosocial Proximity dataset in a mapping and analytics platform from one of our many partners.
Esri users can leverage a pre-built feature service and suite of plug-n-play reports and infographics.
Use the raw data in CSV or GeoJSON format within your statistical analysis software such as Python, R, Tableau, PowerBI, and Alteryx.
Demographics fall short especially when the visitors to a trade area don’t live in that location. Geosocial picks up the volume and activity of a location to capture the full picture of area characteristics.
Enhance predictive models by differentiating demographically similar locations by social behavior. The different behaviors in an area can often explain high and low performing stores that are otherwise demographically the same.
Unlike Census data which can lag up to 10 years, Geosocial Proximity is updated quarterly showing the current and historical trajectory of an area. Keep models up to date with current behavior and know the trajectory of an area to make smart real estate acquisitions.
An overview of how this dataset was built.
People geotag posts about what they are doing or experiencing in a location.
We clean posts and aggregate at the block group to analyze text and hashtags.
Using machine learning we cluster mathematically related words into segments.
We score block groups as percentiles 0 - 100 vs. the nation. Above 50 is above average.
Explore the most common use cases for Proximity.
Reach out to our sales team to see a personalized demo for your use case. Or explore the Proximity taxonomy to see the data for yourself.