Keenan Baldwin, Cofounder of SiteZeus, shares his thoughts on geosocial data.
I was with Keenan Baldwin on a webinar last week when we asked this question. The results blew us away. Of the 90 people who signed up for the webinar, 100% answered YES to this question.
There is more to a community than meets the eye, especially with Retail and QSR site selection. As a platform that literally creates thousands of forecasts for companies such as Subway and Vitamin Shoppe, SiteZeus gets to see this case every day.
After deploying Spatial’s Geosocial data into their models, some real data science magic began to happen. Spatial’s Geosocial dataset organizes billions of social media conversations into 70 actionable segments revealing the personalities of communities down to the block group.
This allows companies to finally quantify the neighborhood personalities that fit their brand. Here is an actual example from the webinar.
Sandwich shop #1, performs 25% below the brand average.
Sandwich shop #2, performs 25% higher than brand average.
Here is the kicker. Look at these two on demographics and traditional data sources.
Notice anything? Yeah, these two locations are nearly the exact same on traditional data. Yet one of these nearly doubles the other in sales. Something else is going on here. Let's look at the Geosocial data for these two sites.
Now we've got something! There are some definite differences here, I’ll point you toward "Blue Collar" and "Urban Fashion." SiteZeus’s model found "Blue Collar" to be a positive indicator for this sandwich brand. This segment consists of people talking about Pilsners and Nascar - very good.
On the other hand, the model found “Urban Fashion" to be a negative indicator for this sandwich brand. This segment consists of people talking about styles and name brands - very bad.
See what is happening here? The site on the left column is the high performer, it has a very high "Blue Collar" score and a very low "Urban Fashion" score. That is a double win because it over-indexes on "Blue Collar," which is good, and under-indexes on "Urban Fashion," which is also good.
The underperformer on the other hand under-indexes for "Blue Collar," which is bad, and over indexes for "Urban Fashion," which is bad.
Let's see this mapped. First, the underperformer:
Under indexes on "Blue Collar." Where as you can see the blue areas would have been a perfect match. So close!
Now let's see the over-performer:
Very high on the "Blue Collar" segment! But as you can see - there might have been an even better spot just north of there.
The insight here? Communities high in the "Urban Fashion" segment do not resonate with this sandwich brand, probably because they have a higher taste palette. This brand fits with the "Blue Collar" segment - which tends to be deal seekers.
To watch us walk through this example, click here.
The mindsets and attitudes of communities have a bottom line impact on the success of your locations.
We are proud to partner with SiteZeus to activate Geosocial data. Click here to check out SiteZeus.