Oct 30, 2019

Introducing Brand Correlations


The Spatial.ai Taxonomy now includes top correlated brands for each of the 72 Geosocial segments. This valuable addition can help Geosocial data users get a better understanding of each segment and the brands that do well when a segment is prevalent in an area.

Explore brands for each segment in the Taxonomy


Since the release of our segment taxonomy and product, we’ve always included information on Geosocial data’s effect on categories of retailers and restaurants (“Coffee Shops”, “Bookstores”, and “Breakfast & Brunch Spots” for instance). We regularly receive feedback that these relationships are some of the most useful data we provide. 


In order to take it a step further, we drilled down deeper than categories and our point of interest data to identify which large national brands have strong relationships with each Geosocial segment.  By providing these brands, we’re giving our customers concrete examples of some of the brands that go well with each Geosocial segment.


brand correlations preview


Analysis & Methodology

To identify the brands that match with each segment, we used latitude and longitude data from our point of interest database to identify brands with many locations and national presence. We considered approximately 1100 brands which all had more than 100 locations in our POI data. Then, we compared median scores for each segment in areas that had these brands to national median scores. To ensure comparability, only areas that pass a threshold of social activity and at contain least 1 national brand were used. Based on these differences in median segment scores, we could identify the brands that had the strongest relationships with each of our Geosocial segments.


The brands we’ve identified each fit 2 criteria: 

  1. They must have a strong, positive relationship with the related Geosocial segment
  2. A brand’s relationship with a segment must be relatively strong when compared to its relationships with other segments (we used a Z-score to measure this, for you stats folk).  


To demonstrate what we mean, the following chart shows differences in median segment scores for areas with Starbucks vs. national median scores. For readability, we’re only showing the top and bottom 5.


image (2)


Starbucks is an interesting case because it has strong relationships with several Geosocial segments. However, due to the second criterion which compares the relative strength of relationships, Starbucks is designated as having relationships to Coffee Connoisseur and LGBTQ Culture.  It is possible for one brand to be associated with more than one segment.


This methodology is designed to produce relationships between brands and segments that not only are proven out in the data but also produce strong stories.



In adding these brands, we’re empowering our customers to use Geosocial data to the fullest. When matching businesses to communities, these brand correlations are a helpful guide. Have a vacancy in an area that scores highly for Green Thumb? Tenants similar to Whole Foods or Walgreens might be a good fit.


Screen Shot 2019-10-24 at 3.24.27 PM


We are excited to release this new information to our partners and customers. With these brand correlations, we’re enhancing the data and people-centric view that anyone can get of a community.


Explore brands for each segment in the Taxonomy


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