Show your customer's exact location

Show points to visualize customer and loyalty data

Cameron Klapwyk avatar
Written by Cameron Klapwyk
Updated over a week ago

Customer loyalty data can be used in PiinPoint to show your customer's contribution by geography levels (e.g. FSA, Block Group) or to look at individual customer addresses, and delineate natural boundaries of where your customers travel from in order to calculate market penetration and visualize cannibalization.

Once you've uploaded your client data into PiinPoint and explored the heat map display of customer contribution, try looking at the data by individual points.

Show Individual Points

In the Layer panel under Contribution & Web Layers, click the Gear icon on the left side of any contribution layer and input the store numbers that you want to analyze, e.g. show data for store 1480 based on FSAs:

Within the Layers Panel, click the option to Show Points. 

Based on the Store ID that was inputted, individual points will appear on the map within each area:

👉 Keep in Mind

  • If you're showing customer data in Canada, the lowest level of granularity that can be shown is by postal codes, even if your data is based on street address. Check out our docs here to learn more about discovering which postal codes have multiple customers.

Map Multiple Stores' Trade Areas

Using the Show Points tool, you can pick up to twenty locations and visualize the spread of your customers for a given market. This helps you identify the organic boundaries of your trade areas, showing which ones customers visit and the opportunities for infill sites.  

Once your customer points are on the map, a legend will appear in the bottom right of your screen, allowing to toggle any of the selected locations customers on and off.

Show Changes in Contribution Over Time

You can also upload multiple samples to see how the spread of your customer changes across different periods of time (e.g. seasons, months, years).

For example, this Sample Store 1480 saw a huge increase in customer distribution from 2016 to 2017, perhaps due to closing a store in North York and increasing the number of targeted ad campaigns run in Etobicoke:


Still have questions about Customer Data and Contribution layers? For a full tutorial on using contribution layers, click here, or find out how to started with Layers here


If you have more questions about Candidates, contact your Customer Success Manager via Chat or email:

Did this answer your question?