This post is part of a series of articles on how CRE professionals can design better, data-backed property strategies with foot traffic segmentation. To learn more, join us for our upcoming webinar, CRE’s New Secret Weapon: Foot Traffic Segmentation.
The first job a tenant representative performs for a client is site selection. There is no better way to set the tone than to show you have done your homework. You need to know the markets where the brand thrives. But the preparation required to find and present properties that meet real estate committee requirements is time-consuming.
Finding the perfect tenant fit and convincing parties of the match doesn’t have to be so challenging. Especially when you can leverage intent signals from social media, cell phone visitation, and online search of the nearby population. The PersonaLive segmentation provides visibility to digital behaviors that help distinguish an average location from spectacular.
Spatial.ai empowers tenant representatives with instant access to data that helps them find the ideal tenant location, overcome concerns of sales and demand, and close deals.
Cutting The Homework In Half
By profiling foot traffic to a brand’s stores, tenant representatives identify the unique online, offline, and demographic traits of the segments that drive success. We call this behavioral mark the Brand Thumbprint. You can identify it in under 30 minutes with no GIS skills. Unlike demographics, it results in an actual metric showing the demand of the local population for the brand.
Let’s look at how to identify a national brand's top segments to create a tenant strategy.
Case Study: Raising Cane’s
If you are working with a national brand, there is a good chance we already have their customer segments pre-calculated. You can rank the top segments that visit a brand’s locations or that follow the brand’s social media account. Or both.
Assume you were hired to represent Raising Cane's Chicken (who plans to open 100 new locations across 10 markets in 2022). Indianapolis is a new market for the brand. You can find their top customer segments in two steps:
Rank Top Segments
Map The Results
Step 1: Rank Top Segments
Go to the “Analyze” tab. Type “Raising Cane’s” in the search box. You’ll see the top families ranked by index. You can break it down further by toggling to Segments.
Step 2: Map Segments
By summing the percentages of the top 10 segments for Raising Cane's, we can get a block group heat map indicating the locations with the highest demand for the brand. This is Raising Cane's brand thumbprint. For the block group highlighted, 92% of the residents are in the restaurant's top 10 consumer segments.
From here, Raising Cane's can determine what kind of flavor of store they want to open based on the trade area. For example, placing a location near the IUPUI campus would capture the 1,238 #College households that are 3.2x more likely to visit the brand. Or they could choose the suburban Noblesville location that has 1,025 #BabiesBurbs&Blessings households with an index of 154 (54% more likely to visit).
Data Closes Deals
Foot traffic has helped CRE professionals gain an edge in landing deals by showing visitor counts to a property. Now that most companies have adopted it, real estate committees need to know the likelihood those visitors will become their customers. PersonaLive helps tenant representatives in three ways:
Unique brand thumbprint: Identifies communities where the online and offline preferences are uniquely suited to a tenant.
Quantifies likelihood to visit: Because people are segmented by dynamic behavior and not static demographics you can show the % likelihood nearby residents will become customers.
Cuts research time: We’ve automated the drudge work. No hardcore GIS skills are required. If you can draw a polygon and add segments to a map you can research like a pro.
Personalive segmentation uses social media, mobile foot traffic, online activity, and individual-level demographics to organize every US household into one of 80 behavioral segments. These segments provide visibility to the online and offline preferences of the customers visiting any US property.
Draw a polygon around a property to identify the behavioral segment of every visitor.
Rank the top customer types visiting a location. Then match retailers based on online and offline activities of visitors.
Demonstrate visitor brand affinity to close deals. Activate marketing campaigns to drive target segments to your location.
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