Research reveals that businesses who prioritize data-driven decisions are three times more likely to improve their strategic decision-making compared to those who don’t.
Commercial real estate (CRE) is a complex sector, with an ever-increasing amount of data available. Understanding how to navigate and synthesize this data is key to success. How do you sift your way through?
In this guide, we take a deep dive into how location data complements demographic data in CRE. We show you how to integrate the two types of data into your strategic decision making.
Understanding the Limits of Demographic Data Alone
Demographic data provides information about people such as where they live and who they are.
Some examples of demographic data include:
- Age
- Gender
- Ethnicity
- Marital status
- Education
- Occupation
- Household income
- Place of residence
- Religion
This important ‘people’ information is useful to CRE professionals because the surrounding population in any given area will be the majority of the customers for the retail stores and office parks located there. For example, knowing how much local residents earn and spend can be invaluable for retailers targeting new locations. While demographic data is plentiful, it’s only a piece of the puzzle. If looked at in isolation it won’t tell the full story.
Location Data Defined
Location data is another key piece of the CRE puzzle. It has two components:
- Geospatial data – essentially maps showing the proximity of properties to amenities and public transport.
- Mobility data collected from mobile devices, like smartphones and GPS devices in cars, which helps track how people move and shop in specific areas.
Examples of insightful location data include:
- Number of unique visitors to a store monthly
- Average visits per day or per hour
- Length of each visit
- Frequency of repeat visits
- Cross visitation patterns
- Area visitation rates
- Most popular stores in the area
- Real-time trade area analysis
- Car traffic
- Consumer spending patterns
- Future forecasts using predictive analytics
This data, when merged and analyzed with geographic information systems (GIS) tools like AlphaMap, provides a holistic view of how people interact with spaces, enhancing the CRE decision-making process.
[Box out: Location data comes in the form of mobile GPS pings from:
- Mobile phones
- Beacons
- Wi-fi networks
- Satellite images
- Connected vehicles
- Other remote sensing devices that keep track of where people and things are]
Synergizing Location and Demographic Data for Enhanced Insights
When location data is linked to demographic information it starts creating a picture of exactly who shops where and when, in your area of study. The key insights lie in understanding how customers behave, over and above who and where they are (which demographics will tell you).
You’re able to really study the market and consumer preferences of a specific site, which becomes extremely valuable for informing strategy, or analyzing potential deals. For instance, real-time location data can pinpoint the ideal site for a new CRE venture, moving beyond intuition to data-backed decision-making.
Additionally, analyzing location data can optimize tenant mixes in shopping precincts, adapting to the actual needs and behaviors of local shoppers.
Location Data in Action
Consider an example of a small shopping center in a suburban center. The shopping center has been around for over 30 years and always relied on a few anchor tenants to keep it going. Over the years, the mix of other tenants frequently changed, and the center has struggled to attract steady foot traffic. A savvy owner turns to the data to improve the tenant mix and attract more foot traffic.
They use GIS to study the location data, the needs of the local population, and the existing stores in the center. They identify a popular take-out chain that would complement the existing stores. The owner studies the mobility data over the next few months and sees that the take-out chain has dramatically increased visits to the center as a whole. More investigations reveal that a stationery shop and hairdresser would complement the mix too, so these are integrated. At this point the shopping center has been completely rejuvenated. All thanks to the power of GIS analytics.
Overcoming Common Challenges in Organizing Complex Data Sets
Merging different data types in CRE can be challenging due to issues like data volume, inconsistency, and complexity of integration. Fortunately, all these problems can be overcome with the right tool.
AlphaMap, a CRE-specific, cloud-based location insights tool, combines GIS with advanced technology to provide a seamless, easy-to-use interface, making it straightforward for users to navigate and access needed information. AlphaMap includes details on over 10 million commercial properties across the US, ensuring coverage for any market. We draw our analytics from more than 40 distinct data sets, delivering the most comprehensive property insights available. Additionally, we gather location data from over 100 million mobile devices to offer precise foot traffic estimates.
Using AlphaMap to merge and analyze location and demographic data is simple. Whether you are researching property deals, studying market trends, analyzing competitors, or assessing foot traffic, AlphaMap makes it easy to derive actionable insights that drive solid decision making.
Final Thoughts on Maximizing Location Data
The synergy between location and demographic data helps to enhance precision in CRE investment decisions, while providing new avenues for innovation. In future, the benefit of being able to adjust and harness comprehensive data analytics will be a differentiator in the competitive CRE landscape.
Tools like AlphaMap flip the perspective from numbers-driven to data-smart investments, holding the potential for great returns and strategic success in the real estate market.
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