Rather than boxing consumers into small subgroups, Geosocial data creates connections between actions and activities, so it reflects that consumers are more than their demographic or psychographic labels.

Just because you have the same demographics around a location does not mean those individuals will behave the same way. Communities have quantifiable social differences. That’s what Geosocial data really uncovers.

Combine Geosocial data with demographics, retail co-tenancy, traffic patterns, and you have a great idea what makes a successful location. This data allows a real estate professional to be a part of millions of conversations with the consumer rather than just one. Powerful.

Retail and restaurant operators often rely on proxies for human behavior and personality as they make real estate decisions. Spatial.ai's socially-driven data provides a new way for organizations to directly incorporate the voice of consumers within trade areas of interest.

What Spatial.ai has been able to capture with this dataset is truly remarkable. They’ve found a large void in the suite of tools available to support location analytics and have filled it perfectly.

Being leaders in the geospatial industry, we intuitively know selecting sites where consumers’ interests and attitudes align with the brand is crucial. Until now, companies have not been able to quantify those characteristics at scale. Geosocial uncovers these characteristics so Esri customers have an advantage in understanding what drives success.