As you click through overlays on a digital map, the expanse of insights pop up in colored areas generated by data analytics. Today’s data analytics tools will show demographics by U.S. Census block: total population, median income, median age, education levels and job categories. But then there is so much more.

Data analytics services, such as MapDash, can quickly display demographic data for any location. Image courtesy of Datastory.

For example, how much is the average household spending and what is that money spent on? What are the predominant lifestyles (affluent estates, GenXurban, midtown singles and others), median home values and rental contracts, daytime population densities and the mix of health insurance types held by residents?

The amount of data that can be presented through web-based apps, customized dashboards or deep analyses generated by Esri (a geographic information software and data provider) is seemingly endless. That presents both opportunities and challenges to CRE professionals who want to use data analytics effectively.

“I don’t think anyone believes there isn’t enough data. It’s more a question of making sense of it. Is it telling a story,” said Matt Felton, Founder of Datastory, a location intelligence firm started in Baltimore more than a decade ago.

CBRE has taken a strategic approach to effectively utilizing data analytics in its practice.

“Our brokers have really good knowledge and gut instincts on the market and a lot of experience helping tenants resolve their location decisions,” said Stephanie Jennings, Research Director for CBRE.

Select data analytics functions, however, have bolstered that knowledge.

“CBRE has internal tools that help brokers keep the pulse of market,” Jennings said. Those tools enable brokers to easily pinpoint deals on a map and assess various aspects of each deal – for example, asking rents versus taking rentals, concessions, similarities to nearby deals, “who is driving market demand and who is conspicuously absent and how does that effect demand.”

Data analytics, she added, reinforce brokers’ recommendations about the best properties for prospective tenants, especially for data-driven clients such as tech companies and financial services firms. In addition to showing market fundamentals, analyses can show where target employees live, how long their commutes would be, plot amenities within the neighborhood and other factors that fit within employers’ current flight to quality or desire to support more balanced lifestyles.

CBRE Mid-Atlantic is also developing a dashboard to track pandemic recovery in key neighborhoods in the region through multiple factors – vacancy rates, employment levels, metro ridership, foot traffic and other patterns that would impact retail.

Commercially available data analytics apps, such as Datastory’s MapDash, enable users to easily layer any combination of several hundred datasets onto a map in order to assess factors that are most important to their location decisions.

Customized location analytics performed by the Datastory team can produce even more granular and focused location intelligence, Felton said. Macro data from cell phones (i.e. data that doesn’t show individual activities) can show the volume and timing of visitors to businesses and other points of interest, show where they are travelling from, and even the patterns and trends in those visitors such as demographics and their consumer habits.

“We can roll up all those stats to reveal insights such as 30 percent of individuals visiting that store are young millennials with high discretionary income that care a lot about eating organic and entertaining. At this other store, they are value shoppers – families with two working parents and long commutes,” Felton said.

Data analytics can go far beyond a baseline of demographics to include insights from consumer psychographics and “the emerging data feeds of geo-social information – what are people Tweeting about, what are their Instagram hashtags. We have begun to leverage this geo-social data to create maps that show what types of cars people hashtag or search for so we can show this is BMW country and that is Honda country,” he said. “It delivers the next level of understanding human consumer behavior. It’s not just knowing that this group on average makes $75,000 a year, but this is how they spend it… Whether you are on the front end of real estate investing and developing or you are involved in property management, leasing, and marketing, it helps you maximize success in finding the right properties and drawing the right tenants.”

Data analytics, he added, becomes especially helpful when a CRE professional or client is dealing with an unfamiliar situation, such as expanding into a new state.

“We are working with a national retailer now that is trying to identify store expansion sites, marketing plans and what products to put in what markets,” Felton said. “We can analyze their best stores – what are the demographics, lifestyle, consumer behavior, traffic – within a five-minute drive of those stores and then identify new locations where those same conditions exist. Whether it is helping a retailer maximize their profits, or enabling a developer to speed ahead of their competitors to win tax credits for a new site, location intelligence gives you this interactive game board that business leaders can use as a differentiating advantage. We believe that once you are able to hear what all the data has to say, you will make better decisions faster, with confidence.”