Part 1: Solving The Leasing Puzzle By Segmenting Store Foot Traffic
June 14, 2022
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.
This is part one of a four-part series showing how CRE professionals and analysts can append social segmentsto foot traffic data, analyze segments visiting a location, and activate marketing campaigns to drive the ideal customer to the center.
Finding the perfect tenant fit and convincing parties of the match can be challenging, especially when the only way to describe the visitors to a location is by their demographics. Spatial.ai empowers leasing professionals with instant access to data that helps them find the ideal tenant fit, overcome concerns of sales and demand, and close deals.
In the past few years, the use of foot traffic data by commercial real estate companies has skyrocketed. Products like Placer.ai and Near’s Pinnacle have used an intuitive interface to unlock opportunities for CRE professionals to do advanced market research.
But finding the perfect tenant fit and convincing parties of the match remains challenging, especially when the only way to differentiate visitors to a property is demographics. Take these two mixed-use properties, for example:
Everything about these two retail properties would indicate we should take the same approach. But appending social segments to devices visiting these properties reveals a different story.
Even at a 17 segment family view we already see major differences in the customer profile. The Newport location has blue-collar and suburban clientele while Atlantic Station has lower-income urban and young professional visitors.
Although demographics are the same, not one behavioral segment overlaps. People visiting these properties have drastically different brand tastes and online activity that we can leverage to create a data-backed leasing strategy and close deals.
Before doing a case study, let's review how to link device visits to segmentation.
Linking Device Visits To Segmentation
Customer data has been linked to segmentation since before foot traffic data existed. Analysts in the 1980s were linking customer addresses from mail-order catalogs to the dominant segment in the neighborhood. PersonaLive uses a similar approach but automates this process for you. Upload a mobile report or draw a polygon to have every device profiled in minutes.
Let’s dive into a case study.
Case Study: Newport On The Levee
Profiling top customers and creating a retail strategy should not take more than 15 minutes. It includes three steps:
Draw a polygon
Identify target segments
Choose retail type
Let’s demonstrate by profiling the foot traffic to Newport On The Levee, a once-popular Cincinnati property that has seen hard times and has many open leases.
Step 1: Draw A Polygon
First, we capture foot traffic visiting a property for a specified time range. Login to the PersonaLive platform and navigate to the Segmentation tab > Select New Report > Draw a Polygon.
Step 2: Analyze Target Segments
Second, we look at the percentage of each segment visiting the property. Navigate to the Insights tab > Select Mobile Insights.
Step 3: Choose Retail Type
Lastly, we need to know the retailers our target segment(s) visit. Click a segment. Navigate to In-Store Visitation to display the cell-phone-based brand visitation for the households in this segment. You can even specify visitation by US region with the toggle in the right-hand corner.
For Newport's top segment, #BabiesBurbs&Blessings, brands like Kid to Kid, Cafe Rio, Snap Fitness, and Cinemark stand out. An index of 100 is average. A score of 305 for Aquariums indicates these households are 3x more likely to visit an Aquarium than average.
No surprise Newport already has an aquarium, which is likely driving this higher income segment to the destination.
Data Closes Deals
In the past, property owners and retailers relied on basic demographics to describe visitors. But demographics are only part of the story, and don’t include important information such as customer tastes. Now, in under 15 minutes, leasing professionals are able to quantify the likelihood the visiting population will become a tenant’s customer. In the case of Newport On The Levee, we know their location’s visitors are 5x more likely to visit Cafe Rio than the national average based on 12-month visitation patterns.
But what if you are representing a tenant and trying to find the right location for them? That is what we will explore in part two.
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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