Site Selection
Find, validate, and prioritize your next best locations.
By the end of this guide, you will have identified the PersonaLive segments that define your best customers, and used them to find, map, and validate at least one new prospective site.
This workflow uses Append, Analyze, Map, Explore, and Cross Shop.
Site selection workflow
Build your segment profile — Everyone starts here. Choose the best method available to identify the segments that define your ideal customer.
Find and validate sites — Map your segments, find concentration gaps, drop pins on prospective sites, and validate. Works for established brands and new brands using a competitor proxy.
Advanced tools and tips — Additional tools and resources to aid your analysis.
Build your segment profile
Before you can find new sites, you need to know which PersonaLive segments define your best customers. Use the highest-quality method available to you.
Tip
If you are a new or emerging brand lacking significant store or customer data, choose a competitor or analogous brand as your proxy when reviewing Credit Card Spend data or when Options 3 or 4 ask you to load locations.
| # | Method | Best for | Requires |
|---|---|---|---|
| 1 | Customer Data Upload | Brands with transaction or loyalty records. Captures your actual buyers directly. | Your own customer file (addresses, emails, or coordinates). |
| 2 | Credit Card Spend | Any brand with transaction volume in the CC dataset. Captures actual buyers—highest signal quality. | Strategist subscription. Larger, established brands only. |
| 3 | Mobile Data | Any brand with existing locations. Captures actual store visitors. | Locations loaded in the platform. Mobile data availability varies. |
| 4 | Radius Rings | Any brand. Captures residential population near your stores—least direct proxy. | Locations loaded in the platform. Always available. |
Note
Use the highest-ranked method available to you and skip the rest.
Option 1: Customer Data Upload
Upload your own customer records to build a segment profile from your actual buyers. Best for brands with loyalty programs, POS data, or e-commerce transaction history. Ideal to have data split by store where possible.
Go to Append → Customer Lists → Upload List.
Upload your customer file. Include customer addresses or coordinates and store ID (if available). Upload two files: one overall list, and one that you will split by store using a Store ID column (the platform will ask if you wish to split on upload). If you'd like to map your customer data, agree to retain data for mapping (recommended).
Go to Analyze. Select Customers in the Source dropdown, then select your uploaded list. In the Breakdown dropdown, select PersonaLive Segments. Review the top segments. Note the top 5–10 with significant percentages and indices over 100—you'll use these in the mapping steps.
Tip
For per-store analysis, select the split file option on your customer files so you can identify which segments drive performance at each store individually, rather than blending your entire fleet.
Option 2: Credit Card Spend
Spend data identifies which segments are actual paying customers at your brand—not just visitors or nearby residents. Outside of your own customer data, this is the highest-fidelity signal for segment identification. Available for Strategist subscribers and larger brands.
Go to Explore → Credit Card Transactions.
Select your brand from the Category/Brand dropdown. If your brand does not appear, it may not have sufficient transaction volume in the dataset. Choose an analogous brand or move to Option 3.
Select the top segments by Revenue Share. By default, you will see PersonaLive Groups. Narrow to PersonaLive Segments for site selection use cases. These are the segments actually spending money at your brand. Note the top 5–10 (percentage and index)—you'll use these in the mapping steps. If you are looking for regional insights, narrow your geographic scope to the closest region, state, or DMA by clicking the market base toggle located under the Source dropdown.
Map your top segments. Click Map in the right side of the table footer, select the top segments (high revenue share and high index), and Confirm & Send to the Map. You can now visualize pockets of the top segments nationally.
Tip
Revenue Share filters out casual visitors and confirms who your real, paying customers are. It's a more precise signal than foot traffic or residential proximity.
Tip
When selecting top segments, pay close attention to those that make up both a high Revenue Share and have a high Index.
Option 3: Mobile Data
Uses movement data from mobile devices to identify who actually visits your locations. Available for any brand with locations loaded in the platform.
Add mobile data in Append using one of these methods:
- Add Brand Locations: Append → Add Location → Add Brand Stores. Select a brand to quickly add locations from our brand catalog. Many of these locations already have mobile data associated with them.
- Upload Location List: Append → Add Location → Upload File. Upload a CSV of your locations. Mobile data is linked automatically if a Brand column is included in the file and we're able to match it to our existing mobile data. Include performance metrics such as store sales as custom fields so you can organize and analyze locations by performance.
- Upload Mobile Report: Append → Mobile Reports → New Report → Upload Report. Upload one or more reports from your mobile data provider.
If you uploaded store sales, sort by that metric, select your top-performing locations, and create a group from the bulk action toolbar.
Go to Analyze. Select Visitors in the Source dropdown, then select your top-performing locations or mobile reports. In the Breakdown dropdown, select PersonaLive Segments. Note the top 5–10 segments (percentage and index)—you'll use these in the mapping steps.
Option 4: Radius Rings
Analyzes the residential population within a set distance of your locations.
Add locations in Append using one of these methods:
- Add Brand Locations: Append → Add Location → Add Brand Stores. Select a brand to quickly add locations from our brand catalog.
- Upload Location List: Append → Add Location → Upload File. Upload a CSV of your locations. Include performance metrics such as store sales as custom fields so you can organize and analyze locations by performance.
If you uploaded store sales, sort by that metric, select your top-performing locations, and create a group from the bulk action toolbar.
Go to Analyze. Select Trade Areas in the Source dropdown, then select your top-performing locations. In the Breakdown dropdown, select PersonaLive Segments. Note the top 5–10 segments (percentage and index)—you'll use these in the mapping steps. Take note of the total count of each top segment by population and compare this to low performers. You will use this to set a threshold of how many of each segment you need to replicate top performing sites.
Note
Radius rings reflect who lives near your stores, not who visits or buys. For destination brands or those in mixed-use areas, this can overweight segments that are geographically close but not actual customers.
Find and validate sites
Now that you have your target segments, use them to find new markets and validate prospective sites.
Map your target segments
Go to Map, open the Heatmap layer panel, and select up to 10 of your top segments from Step 1. Only select segments with an index above 100—these are the ones overrepresented among your best customers vs. the general population.
Tip
For real estate decisions, always use Segments, not Groups. Segments capture behavioral nuances that Groups smooth over, which matters when replicating specific store performance.
Note
The map now shows a heatmap of your selected segments by Census Block Group, Zip, or DMA. Darker shading means higher concentration of your target segments.
Overlay your fleet
Open the Locations layer panel, and select your locations to add them to the map. This surfaces proximity gaps—areas with high segment density that don't yet have a nearby store. These are your highest-priority prospecting zones.
Note
New or emerging brand using a competitor proxy? Overlay the competitor's locations here instead of your own. You're not trying to locate next to them—you're using their presence as a signal that your shared target segments exist in that market. Look for areas where your segments are concentrated but competitor coverage is thin.
Drop a pin on a prospective site
In the top left of the map next to the search bar, click the Location Plus toggle, then click on the map to drop a pin. Place a pin in an area dense with your target segments and not already covered by your fleet.
When you place a pin, the segmentation results for that location will automatically appear. Analyze segment fit within a 3-mile radius by percentage and total household count. Click Save to keep it for evaluation.
Note
What does good look like? A segment fit of 60–70%+ within a 3-mile radius is a strong signal. Additionally, you need to ensure there is enough population of the target segments nearby to support a site. Compare the population of each segment to your top performing stores to determine the required threshold.
Validate with Mobility Grid
For Mobility Grid subscribers: In the Heatmap layer panel, select Mobility Grid from the View mode dropdown to surface hexagons showing where your top segments actively spend time—not just where they live.
Remove Highways and US Routes unless your concept depends on highway access. This confirms target customers actively frequent the area, not just reside nearby.
Validate with mobile data (custom polygon)
A radius around a pin shows who lives nearby. For sites where the real visit footprint is a building, center, or irregular shape, pull mobile data for a custom polygon instead—so you can confirm your top segments are actually visiting the place, not only living in the surrounding area.
For example, if you are considering a space in a shopping center, draw a polygon around the center, run a mobile report for that boundary, then check in Analyze whether your target segments already visit the center.
Go to Append → Mobile Reports → New Report → Create Report. Search for the site and click Draw Polygon to outline the shopping center (or other boundary).
Select Next, choose the timeframe for analysis (12 months is generally a good rule of thumb), name the report, and create it.
Wait until processing finishes (up to a couple of hours; you receive an email when it is ready). Then go to Analyze, set Source to Visitors, select the new mobile report, and set Breakdown to PersonaLive Segments. Compare the visitor mix to the target segments from Step 1.
Note
Analyzing custom polygons requires Credits. Purchase Credits from the Buy Credits button on the polygon tool.
Validate co-tenancy with Spend data
For Strategist subscribers: if the prospective site is within a shopping center or mixed-use development, use Spend data to check that the existing tenant mix already attracts your target segments.
Navigate to Cross Shop → Credit Card Transactions.
Review which brands your customers cross shop. Compare these to the anchor and neighboring tenants at your prospective site.
Strong overlap means built-in foot traffic from day one. Weak overlap means your customers may not already be visiting the center.
Advanced tools and tips
When to prefer a custom polygon
Use polygon mobile reports whenever a circular radius misrepresents the visit area—indoor malls, shopping centers, transit-oriented sites, dense urban blocks, or other irregular footprints. See Validate with mobile data (custom polygon) for the full steps.