There are four primary steps to consider with designing, balancing and optimizing sales territory alignments. Get...
Reporting on sales or service performance on a smaller scale using ZIP Codes is important for many organizations such as retail stores, real estate agencies, and restaurant franchises. When faced with reams of data in a spreadsheet, it can be difficult and time consuming to present this data in a way that will show the overall performance of your market while allowing everyone to understand and derive insight from it easily.
ZIP Code Heat Maps use color to reveal different levels of intensity - for example, the number of customers and sales revenue within a certain ZIP code. They are a great way to provide an overview of your market.
With eSpatial, you can quickly create powerful ZIP Code Heat Maps that highlight data intensities within ZIP code boundaries.
Why create heat maps from ZIP codes?
As we mentioned above, many of the customers who use ZIP Code Heat Maps work in retail, real estate, or franchising. This is because ZIP Code Heat Maps allow them to get a more granular view of their sales or service performance than state or counties would allow.
Here are a couple of examples of how ZIP Code Heat Maps are helpful when analyzing performance, identifying opportunities for expansion, or planning targeted direct mail drops.
Below is an example of a Menswear Retail Store and how they use eSpatial ZIP Code Heat Maps to identify opportunities for new business.
- Carry out a ZIP code heat map of your customers.
- Filter the data to show only the ZIP codes with the highest volume of high-value customers.
- Export that list of ZIP Codes to CSV so that you have them to reference later.
- Return to your map and clear your regional heat map analysis.
- Turn on Color By Value on the Demographics ZCTA Dataset you use for your ZIP Code Boundaries.
- Filter your data to the ZIP codes that you exported earlier.
- Analyze the demographics of those ZIP codes using the data in the table to identify any similarities, for example, 10% of the populations of that ZIP code are 30-39 Year Old Males.
- Note down the similarities and clear the filter on the ZIP codes to show all ZIP codes in that county.
- Now filter the demographic data to only show ZIP codes with 10% or higher populations of 30-39 Year Old Males.
- Overlay this with your customer location points.
- You can now see on the map ZIP code areas where you do not have any customers but have a high density of your target market. This could mean opportunity for a new store, or a targeted mail drop in this ZIP codes to generate more business for your existing stores.