Study Highlights Location Data Uses in Real Estate, Retail Analysis, Smart Cities | Street Fight

Study Highlights Location Data Uses in Real Estate, Retail Analysis, Smart Cities

Study Highlights Location Data Uses in Real Estate, Retail Analysis, Smart Cities

Escalator

Location intelligence firm Cuebiq released a study this morning showcasing the kind of deep location data that its platform can reveal. For a month, Cuebiq tracked geo-behavioral patterns of anonymous consumers in the Westfield World Trade Center (WTC) shopping mall, right after the mall’s grand opening in August. The study differentiated between tourist and local visitors, and the most interesting piece of data that showed up was about consumers’ top three favorite brands.

Analyzed visitors showed the strongest brand affinity for brands Zumiez, Prada, and Best Buy. But none of those brands were located in the Westfield WTC mall. This indicates potential for the mall to increase foot traffic by adding those stores to the location. Cuebiq’s data analysis also showed that Sundays were the most popular day at the mall, and Thursdays the least popular.

The platform links with mobile apps and leverages their privacy settings for GPS and public Wi-Fi networks to gather data about where consumers come from, how much time they spend at points of interest, and where they go afterward.

Cuebiq CEO Antonio Tomarchio told Street Fight that initially most of the company’s revenue came from the advertising sector, but now a third of it is coming from non-advertising markets such as commercial real estate planning, retail analysis, and finance.

“I’m here in Austin at a commercial real estate development conference,” said Tomarchio. “I’ve been here for three days and I can tell you, the appetite for this type of data is massive.”

Tomarchio says that this detailed level of data also provides specific reasoning that can help developers and marketers make decisions – such as when to push advertising offers out, and how far away from the point of interest location a campaign should target customers.

“How many miles did [the consumer] drive? Where did they go after they left my store? If you are a retailer or quick service restaurant and you’re planning to open new store, how do you choose the exact location of where to place the new store? Until now, companies were using data from surveys, but surveys are static. You do it once and you don’t do it again for three or four years,” Tomarchio says. “Now … it’s basically in real time.”

Today’s retailers already know a lot about their customers, thanks to customer relationship management (CRM) software, but Tomarchio says that most of the time, once the consumer leaves a physical location, the brand loses touch.

“Who are those customers, what do they do in the physical world when they leave the store?” he asks. “Do they go to my competitor? What’s their brand visitation frequency? What interests them in the physical world? Are they movie-goers? This gives true details about the audience. It’s very useful for considering promotions or ad campaigns.”

Cuebiq’s data basically enriches CRM systems with data about what consumers do once they leave the store. Tomarchio says about 80% of Cuebiq’s data has location accuracy to fewer than 10 meters, and with that kind of accuracy the opportunities are immense.

“With our data we can understand the flows of car traffic, or if pubic transportation is working properly, we can understand the commuting patterns of people who are commuting to a city,” he says.

Tomarchio also says he knows what vertical this kind of data will be essential for in coming years.

“Smart city planning,” he says. “That’s where we’re going with leveraging this.”

April Nowicki is a Street Fight contributor.