Fresh Data Blog
Fresh Data Archive
Data Analytics and the Pitfalls of the Zip Code
Date: February, 2014 --
The life of
an analyst whose data includes the zip/postal code can sometimes get
rocky. A recent story from Level Plains,
Alabama underscores the conundrum of data being applied in ways that aren’t
consistent with the purposes for which the data was created in the first
place. In short, we need to be sure that
the application or use we make of the data is consistent with the purpose for
which it was created. Here is a real dollars-and-cents example of this.
The USPS Zip code system was
implemented in the ‘60’s, but has a longer history. During World War II, many experienced postal
workers were called to serve in the military. These were replaced with workers
who were unfamiliar with the structure of the mail sort and delivery system. In
order to remedy this, the USPS developed an elementary single digit coding system
that was applied to urban areas to enable the new “fill-in” postal workers to
sort mail efficiently.
mail volumes, along with the overall economy, began to boom after the war, the
USPS turned careful attention to the logistics and logic of mail movement and
separation. Zip codes were a natural development from the war-time experiment. The
object was to make the USPS more efficient, and faster, in collecting, sorting,
and delivering mail.
back from this vantage point in 2014 when a letter posted in Augusta, Maine in
the afternoon on Tuesday will be delivered to an address in San Francisco on
Wednesday, Thursday latest, the results were nothing short of astonishing. And
all for 49 cents. And although it’s not 46 cents, it’s still quite a
bargain. Nowhere else in the world would
this happen, for that price.
The Zip code system plays a very key
role in that progress. Mail can be directed optimally from any location to any
location. It’s not for nothing that the USPS have one of the most robust and
largest data processing capabilities of all government agencies.
However, what sometimes gets lost in
admiration for the Zip code system is that it was not intended to have the zip
coded areas conform to anything other than the structure of the USPS delivery
system, and that doesn’t always match city-town-county or even State lines. In
short, the ZIP code system is based on mail volume, postal area size, geographic
location and topography, but is not necessarily bound by municipal or community
And here is where Level Plains
enters the picture, joining a fair number of other jurisdictions, by the way. Level
Plains’ addresses, which the town uses to assess taxes and the like, are
assigned through the ZIP system to the neighboring towns of Daleville and
Enterprise. Poor Level Plains doesn’t
exist as a “postal data point”.
a result, there is a great deal of “leakage” of tax revenue from Level Plains. Some
of this is caused by modern accounting software, which applies tax and fee
calculations according to Zip code, not according to street address, and that
software is applying Daleville and Enterprise rates to Level Plains addresses. Some
well-intentioned Level Plains tax payers are inadvertently applying the tax
calculations of neighboring towns through incorrectly organized accounting
software. And these rates are apparently lower than those of Level Plains. The
solution of course is to give Level Plains its own Zip code and the USPS has a
process to examine doing this.
Why should this matter to marketers?
Because your own customer and prospect data may inadvertently locate addresses
in the correct Zip code but in an incorrect demographic or geographic location
you may not want to address. If your client is a fast-food chain, for example,
mailing solely by Zip codes may cause you to waste a lot of money.
Segmentation by postal walk would go a long
way to solve that problem, of course. With
modern household data, an overlay and subsequent analysis of household
characteristics on top of a Zip code map might show some surprises worth
In any event, to perform effective
business intelligence yielding data analysis, and ultimately to get your mail delivered to its intended target, you’ll need properly
standardized, accurate address data, with correct Zip codes, ideally down to
Zip +4. Look to Data Services to provide
those domestic and international data quality and enhancement services critical
to your success!