Census vs. Postal - Which System is Best For Territory Design?

See our sales territory maps page for an overview of all of Maponics’ sales territory related services. Additionally, our sales territory design, creation and mapping page provides information on why you should choose Maponics, and our sales territory design process page details specifics about the techniques we employ.

PRO CENSUS

The US Census Bureau uses census blocks and census tracts to break up the country so it can measure population and other demographics every ten years. In each intervening year, this organization releases demographic estimates based upon the original statistics and estimates of growth. Although the demographics of census tracts and block groups change over time, the boundaries of each are quite stable. Boundary stability is an important consideration when deciding how to delineate your sales territories. When you choose a unit that has less stable boundaries, you are often tied to a more rigorous update cycle.

Since the USPS changes its postal database frequently, the ZIP code level of geography is very unstable. ZIP codes are added, deleted, or reformed somewhere in the United States every day of the year. This results in an amorphous building block that makes territory creation very difficult to stabilize over even short periods of time.

Sometimes, your organization may have legal restrictions for staying within a county or a state.  Because ZIP Codes sometimes cross counties or states, you would need to stay with Census geography.

Demographic data is more readily available at the census level of geography. This is how the census data is compiled by the US Census Bureau and any conversion to postal takes time/resources and may have additional inaccuracies due to the estimation needed to complete the geography as discussed above.

Census geographies are created to have about the same amount of population in each tract or block group. Postal geography is not as closely tied to population and can have large discrepancies from ZIP Code to ZIP Code.

Each cenus tract or block group has a unique coverage area, and every place in the country is covered. ZIP Codes can contain other ZIP Codes (for example a standard ZIP Code containing a P.O. Box ZIP Code). Also, there are gaps across the country with no postal delivery, which will create continuity issues with respect to territories.

PRO POSTAL

Postal geographies may require more hand-holding due to the dynamics of the data that creates them but they are also far more identifiable by the average person. People do not typically know which census block, block group, or census tract they live in. Therefore you tend to lose familiarity when dealing with census geographies. The exceptions of course are the state and county level but in many cases, territories may call for smaller cells as the building blocks.

The USPS offers significant discounts for direct mail efforts focused on mailing to ZIP Codes and carrier routes. List data and counts are more easily discussed using postal terminology.

Is There a Way to Equate Postal and Census Geographies?

Postal geography – ZIP Codes, carrier routes – and Census Geography – tracts, blockgroups – were designed for very different purposes and thus postal and census geographies do no line up with each other.  Depending on your business needs, one may make more sense than the other. But what if you have some customer data by ZIP Code but need to produce more stable territories using census tracts?  Or what if you have demographic data by blockgroup but want to coordinate a direct mail campaign by postal carrier route?

There are several approaches that can be used to equate postal geography with census geography. In fact, Maponics employs a unique methodology to generate accurate demographics at a carrier route level. (We actually combine several methods in an intelligent system to integrate the two and for proprietary reasons that won’t be fully explained here.)

One way that some other companies use is to just assign values based on the center points of each polygon.  For example, if the center point of a postal carrier route falls inside a particular census tract, then that carrier route would inherit the values from the tract. Clearly, there are limitations to the accuracy of this approach most notably the fact that using center points alone may ignore large portions that are outside.

Conversely, another approach is to assign values based on cases where the areas of each polygon are used to produce a proportional overlay of the values.  For example, if 30% of a particular postal ZIP Code overlaps with a particular census blockgroup, then assign that ZIP Code 30% of the values from the blockgroup.  But this approach, in isolation, would ignore the fact that the blockgroup itself may overlap multiple ZIP Codes.  Mathematically, this problem becomes exponentially difficult to calculate.

Maponics has developed a unique approach to this problem that balances the various methodologies. And we’ve compared our values to the approaches from other companies and are confident that our solution is the most accurate.  However, there are limitations to the types of values that can be cross-correlated between two fundamentally different sets of geography. Most notably, only statistical values can be assigned. Attributes such as average household income can be assigned accurately this way but exact population could not. Median age could be assigned this way, but the number of males over the age of 50 could not.  That’s because in the real world, people don’t live in polygons.  They live in houses and apartments and cartographers/demographers group them into polygons for ease of analysis.  If 90% of the people live in the northeast corner of a polygon, raw quantities could not be assigned to other geographies that have a different origin.  But since averages and medians are already statistical beasts, they lend themselves to an accurate representation by skilled mapping experts.

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