How Location Analytics Can Pull Commercial Real Estate out of the Darkness

Decision makers in the $15 trillion commercial real estate industry are forced to make huge decisions based on insufficient data. Surveys are expensive and slow. Other data sources are biased and limited, leaving professionals flying blind on choices worth tens of millions of dollars, or more.

Mobile location analytics, a recent entry into the field, is changing this picture dramatically by providing unprecedented visibility into consumer behavior. Location analytics collects data on the movement of individuals and presents it as an aggregate picture. Where do people shop? What days do they go to a specific restaurant and at what time does that restaurant see the most visitors? How did they get there and where did they visit afterward? This unique ability to visualize movement provides strong behavioral data that underlies performance.

By showing real-time and accurate insights into the movements to and from any place, this data can surface real trade areas, customer journeys, brand preferences, cross-shopping and much more. The change is hugely significant as it finally empowers the industry to make data-driven decisions on the questions that define success for their business. From acquisitions to leasing to marketing and operations, location analytics brings commercial real estate out of the dark.

Here are some examples of how location analytics drives success in commercial real estate.

Accurate Knowledge – True Trade Areas

Anyone who has spent time in the competitive commercial real estate industry knows many of the professionals rely on gut instinct to inform significant decisions. By leveraging location analytics, professionals can put proven rules and concepts behind their gut feelings to help make these concepts more tangible and widely applied.

One example of location analytics in action is the examination and identification of trade areas. Without the specificity provided by location analytics, companies are forced to take a generic approach to their trade area analysis. The basic assumption is made that an audience exists within a radius that extends a certain number of miles beyond the actual store site. However, analyzing true trade area data consistently shows that top retailers often miss major opportunities to expand their audience and drive more sales. A generic three-mile radius ignores critical physical and demographic factors that can determine where a property’s audience actually originates.

Example of a true trade area for two California based properties that show a variety of unexpected realities.

By looking at foot traffic patterns, a company can finally know – and not guess – where their audience comes from. This has huge implications for how they spend marketing budgets, where they build their next store, or even how they analyze their competitive landscape. Location data goes beyond guessing and allows professionals to create an accurate picture of their audience behavior.

Maximizing Investments – Property Acquisition

A simplified analysis of the cost to buy and develop a shopping center estimates the investment at $25 million, on the low end of the spectrum. With this large financial stake, a developer should look to see major returns, as the cost of failing is significant. What is the health of the prospective center’s tenants? How do they rank compared to national and local benchmarks?

Comparing two shopping centers in New Jersey by their weekly foot traffic.

Obtaining objective data that can be applied to all cases is a huge asset. To begin, an investor can develop data-backed parameters on which factors drove success on previous sites. Is the proximity of a customer segment’s workplace the key to success for a specific location? Is the most important factor the mix of tenants, or the overall number of foot traffic nearby? Putting a number behind these components can help developers identify ideal properties and turn those properties into successful entities faster than ever before.

Analyzing two shopping centers based on the time visits take place.

The ability to identify the high opportunity sites and apply effective strategies to them based on set performance data can be a defining trait in driving success.

Analyzing Competitors and Benchmarking Performance

In order to maximize the potential of any property, it is crucial that the property owner understands the behavior and trends of the target audience. Point of sale data, or even counting cars in a parking lot, can provide strong indications. The lack of access to competitor information provides a limited picture. Without location analytics, a property owner cannot answer key questions: How does this property stack up to similar ones in the area? Is a store being negatively impacted by a wider trend or is there something happening at that specific site that needs to be fixed?

Using a single source of data to understand all properties enables an “apples to apples” comparison that reduces biases and improves the quality of decision making. It also empowers true competitive intelligence which enables retailers, property developers and more to gain deep insights into the strategies that drive results. The ability to reveal competitor strategies is a massive opportunity to improve processes and bottom line performance.

Understanding Customer Behavior

Understanding the customer is the Holy Grail of commercial real estate. Seeing how people move, interact, and engage positions retailers and property owners to create the experiences that will drive revenue. It allows developers to invest in high-quality sites, identify better tenants and empower those tenants to more effectively engage with their audience.

In pursuit of this goal, a recent trend noted in top flight data platforms is a wider spread of objective and representative data points that can provide critical customer insights: Time of visit, pre and post visit locations, cross-shopping and more can provide a full and objective picture of customer behavior that can power better decision making.

Targeted Marketing

Another core use for this data is marketing. From a marketing perspective, location analytics can help determine the ideal type and timing of a marketing event, the placement of a billboard or the focus of a targeted ad campaign. Why? Because location analytics tells you where your customers are actually coming from and gives strong indications as to the new audiences you can attract.

For example, analyzing a true trade area can not only tell you where your visitors are coming from but also the areas and audiences that you’re missing out on. The ability to target specific areas – whether by digital or offline advertising – with specific messages can prove a resounding success. Visitors from core areas should receive information that incentivizes them to keep coming back, whereas areas with low visit rates should have offers that push an initial engagement. The ability to segment areas and visitors by such detailed information is a boon for the type of focused marketing efforts that drive real value.

True trade areas for two competing personal electronics locations in Florida showing where customers are coming from.

Measuring performance is also critical when attempting to optimize marketing efforts. If you are having a big sale, does it help produce one time visitors or those who return over time? Are there local events that provide new opportunities to engage customers? They say that people “vote with their feet,” so utilizing analyzing location data is the equivalent of understanding what worked and what target audiences really want.

Optimizing Tenant Mix – A Key to Shopping Center Success

A healthy tenant mix will ensure the long-term health of a center by providing stable revenues and long-term growth. The best way to bring in the right customers is to ensure you have the right tenants. From understanding how different retailers work together to creating richer profiles of which tenants attract the right audience, mobile data can be a critical asset in understanding and maximizing your tenant mix. Considering factors like cross shopping between different retailers and even peak times can help ensure that all stores benefit from the center’s mix. Using location analytics, one developer even found that focusing on complementary players in terms of peak hours helped to ensure enough parking for customers while supporting retailer sales during their non-peak periods

On the brokerage front, it can help convince a new tenant that your shopping center has the ideal mix of people to help drive sales in a site. Location data can alleviate fears of cannibalization, prove the quality and fit of a local audience and even demonstrate demand and potential success for a prospective tenant.

Data is transforming the way that businesses operate and the next logical transformation is coming to real estate. Buy channeling objective, accurate location insights businesses from across the CRE spectrum can maximize their chances of success and identify the opportunities that can drive the next wave of growth.

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