Retail Analytics

Part 2: Tenant Representation – Discover The Brand Thumbprint

Lyden Foust

|

June 16, 2022

This is part two of a five-part series showing how CRE professionals and analysts can append social segments to foot traffic data, analyze customer 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 tenant representatives with instant access to data that helps them find the ideal tenant location, overcome concerns of sales and demand, and close deals.

The Challenge

The first job a tenant representative performs for a client is site selection, starting with a needs assessment from the retailer. This includes requirements like square footage, property type, parking, and demographics. Retailers have varying levels of site selection sophistication and may lean heavily on the advice of the tenant rep. 

As a tenant representative, 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. With demographics alone, it is nearly impossible to differentiate an average location from spectacular.

Cutting The Homework In Half

Spatial.ai empowers tenant representatives with instant access to data that helps them find the ideal location for their tenant, overcome concerns of sales and demand, and close deals. By profiling foot traffic to the brands best 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 how likely the local population is to show up on the brands doorstep based on historic foot traffic data.

Let’s look at how to identify a tenant’s top segments and find their best locations for emerging/regional and national brands.

Case Study: Serena & Lily Tenant Representation, Emerging & Regional Brands

Emerging and regional brands often don’t have a large enough footprint to justify spending time or money on analytics. Here is where the tenant representative can step in and provide value. Identify the top customers for emerging brands in three steps:

  1. Profile Their Best Stores
  2. Analyze Top Segments
  3. Map The Results

We will be representing Serena & Lily for this case study, an emerging furniture retailer with 15 locations across the US who wants to move into the Indianapolis area. 

Step 1: Profile Their Best Stores

Start by asking the Serena & Lily team to share their top-performing stores so we can see the customer profile. We will use foot traffic counts as a proxy for success and analyze these five locations:

  1. 220 BOYLSTON STREET, CHESTNUT HILL, MA 02467
  2. 332 MONTAUK HWY, WAINSCOTT, NY 11975
  3. 101 N. COUNTY ROAD, PALM BEACH, FL 33480
  4. 4430 MCKINNEY AVENUE, DALLAS, TX 75205
  5. 3720 CAMINITO COURT, SAN DIEGO, CA 92130

We draw a polygon around these locations to profile foot traffic. Navigate to the Segmentation tab > Create New Report > Draw a Polygon. Type in the address and draw a polygon around that location. Do this with all five stores.

Step 2: Analyze Top Segments

Navigate to the Insights tab > Mobile Insights on the left sidebar. Selecting the locations we just ran shows the top segments and families visiting Serena & Lily.

25% of Serena & Lily’s customers come from the “Sunset Boomers” segment. With an index of 587, they are almost 6x as likely as the average person to visit the brand. We now have a customer thumbprint to find in Indianapolis.

Step 3: Map The Results

Our top segments for Serena & Lily are Sunset Boomers, Ultra-Wealthy Families, and Educated Urbanites. All three are 5x more likely to visit than average. Combining these segments gives us the unique brand thumbprint. When mapped, the thumbprint shows us the top locations for Serena & Lily in any market in the country.

Serena & Lily Thumbprint

The map above shows block groups with the highest population of Serena & Lily’s top customers. In this case, these people are 5x more likely to visit Serena & Lily.

Using the thumbprint, we can drop into any market and see which locations have the most Serena & Lily type customers. The analysis is done in under 30 minutes. We also did a market selection case study with this retailer.

National Brands

If you are working with a national brand, there is a good chance we already have their customer segments pre-calculated. Step one is complete. Navigate to the Insights tab, and type the brand of interest into the search box to rank segments. Now follow steps two and three as above. 

Read the full national brand case study with Raising Cane's.

Data Closes Deals

Foot traffic data 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:

  1. Unique brand thumbprint: Identifies communities where the online and offline preferences are uniquely suited to a tenant.
  2. 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.
  3. Cuts research time: We’ve automated the drudge work. No hardcore GIS skills are needed. If you can draw a polygon and add segments to a map you can research like a pro. 

But once the tenant is positioned in the right community, how do you activate marketing to the nearby target segments to let them know? That is what we will explore in Part Three.

Want to learn more? Watch the on-demand webinar.

How PersonaLive Segmentation System Works

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.

01 Append

Draw a polygon around a property to identify the behavioral segment of every visitor.

02 Analyze

Rank the top customer types visiting a location. Then match retailers based on online and offline activities of visitors.

03 Activate

Demonstrate visitor brand affinity to close deals. Activate marketing campaigns to drive target segments to your location.

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