Spatial.ai’s Geosocial Datasets Capture a Community’s Personality
Even with all that we’ve learned since 2016 about weak protections on consumer data privacy in the United States, people still love social media and reveal a ton of personal information in the course of all that posting, sharing, and liking.
The insights gleaned from the wealth of social media data are fueling a number of new companies that use them to help their clients with decision-making. One such company is Cincinnati-based Spatial.ai, a startup that did a 2016 stint in the Techstars Detroit mobility incubator program.
Spatial.ai has created artificial intelligence software that uses location and de-identified social media data to understand how people act. The company uses its findings to develop “personality profiles” of neighborhoods and local points of interest, and then works with retailers, restaurant owners, and other customers in search of the best place to open a new location.
Spatial.ai CEO Lyden Foust says his company’s competitors tend to build extrapolated psychographic profiles. For example, Foust says if a person makes an annual salary of $100,000, that person’s preferences will be applied to others with the same income level to create a profile, creating a less-than-accurate picture. “With ours, it’s actual data—we don’t extrapolate the results,” he adds.
Here is an example in which non-extrapolated data might turn out to be more useful, according to Foust. Say a city has a neighborhood that has the income and age demographics a prospective health food retailer is looking for. What that data wouldn’t reveal is that, on social media, a different, less-resourced neighborhood across town could be talking often and enthusiastically about health and food, meaning they might be more loyal or ardent customers.
I ask if Foust has Detroit’s Whole Foods store in mind. When it opened in 2013, many were skeptical that it would last, but it’s now one of the supermarket chain’s more successful U.S. locations.
“Whole Foods is really good at this stuff,” Foust says. “The demographics in Detroit indicated it was not a Whole Foods location, but now, they’re killing it.” What Whole Foods saw was an opportunity in an area that wasn’t exactly flush with big chain grocery stores, he points out, and one that seemed resurgent.
Spatial.ai combs through Twitter, Facebook, Instagram, Flickr, and sites that list local events to find out what neighborhoods and cities are talking about to help customers be as insightful as Whole Foods was in Detroit. “The big thing is that we’re now able to quantify the emotions and mindset of a community,” Foust says.
Aside from using this data to guide site selection choices, it can also be used by municipalities to direct future expansion projects. Foust cites another example close to the heart of Detroiters. When I-75 was constructed through the Motor City in the 1950s, city planners razed the Paradise Valley and Black Bottom neighborhoods, bustling cultural centers for the city’s African-American population, to make way for the project.
Urban renewal, as it was insultingly referred to, was a popular practice despite its devastating effects on the people living in the targeted areas. Many feel Detroit has still not fully recovered from the economic and social disruption caused by the construction of I-75 and its downtown loop.
“Social connection reverberates out into the economics of an area,” Foust says. “Using data like ours, it’s more about how you socially design a city.”