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Modeled Auto Data

Posted by Brian Berg Google+


Modeled automobile mailing lists defined


Modeled automotive mailing list data is mailing list data that’s been created by using modeling techniques to closely identify the consumers within the U.S. who own specific make and model cars.  This mailing list contains names and addresses of people along with their associated automobile ownership.  It is not exact in accuracy but a computer technician’s best guess as to predicting who drives what kind of vehicle.


Why use modeled mailing list data?


The Department of Motor Vehicles maintains a database of all the drivers in the country, their ownership information, and the current mailing address of these individuals.  When you buy are sell a car, this information is added to this very large database.  Before the turn of the century, direct mail marketers could easily gain access to an automotive mailing list selectable by make, model, and year built of the vehicle sourced from the DMV database. 


This mailing list was a great sales lead tool for both auto dealerships marketers and automotive repair service centers. The assumption made was that car owners who’ve owned their vehicle for a few years were more likely to want to upgrade their vehicle than someone who more recently purchased a vehicle.  Likewise, someone driving a utility vehicle is more likely to purchase a utility vehicle again. Other assumptions were made such as purchasing a new vs. used vehicle would do the same again.  Someone paying on a car loan vs. leasing would do the same again, and someone owning a domestic or import are more likely to do the same.  In short, consumers are creatures of habit so designing a mailing list to fit a direct mail campaign was easier in the last century than it is today.


Renting this type of mailing list data for direct mail marketing purchases came to a halt in the year 2000 because too many consumers complained that building a mailing list in this nature for direct mail purposes was invasion of their privacy.  So the next best thing was to attempt to attempt to build a “look-a-like” mailing list that accurately identifies the car owner, and is constructed legally.


What is the Shelby Bill?


In 1999, Senator Richard Shelby (R-AL), Chairman of the Senate Transportation Appropriations Act certain amendments to the DPPA of 1994.  In June of 2000, the Shelby Bill was enacted restricting the use of Motor Vehicle information for research purposes only.  This means that you can no longer build a mailing list of auto owners using the DPV database to be included in your direct mail campaigns. 


Auto dealerships used to using such mailing lists had to find an alternative mailing list.  A foreign car repair center used to using a mailing list of Mercedes and BMW’s had to reconsider their approach to direct mail marketing. The Shelby Bill DID say that marketers could use historical mailing lists, meaning that any mailing lists created “pre-Shelby” were still usable.  This loop hole allowed businesses to purchase historical mailing lists and so long as the car owners didn’t sell their vehicle, this mailing list was perfectly accurate. 


The mailing list was updated with the NCOA process to keep in time with people relocating, but one could assume that the over time, more and more car owners would sell their vehicle and purchase a new vehicle making the historical mailing lists less and less accurate.


How does modeling work? Another carefully worded part of the Shelby Bill said that current DMV information could still be used for research purposes.  This meant that mailing list compilers could look for patterns within the database of current auto owners and construct a new mailing list that resembles the real thing.  For instance, they might find that the majority of pick-up drivers were men and the majority of mini-van owners were women.  This is simple example of a possible pattern but with today’s mainframe technology, the computer can look for many other patterns that would be considered “statistically significant”. 


It’s these statistically significant identifiers that have allowed compilers to boast modeled mailing list accuracy of 80% to 85% accuracy on make, model and year built vehicle ownership. Modeled automotive mailing list data leverages current auto registration information at a local market level in conjunction with household demographic information.  By doing so, it enables the auto dealership direct mail marketer to confidently target their best sales leads based on what is likely parked in the garages in their geographic territory.


What about self report data?


Another way to identify car ownership when compiling a mailing list is through survey data.  Those only a small portion of the U.S. population participates in survey’s, but when a car owner completes a survey, you can bet that their self-reporting of their vehicle will ultimately make it’s way onto a mailing list.  Survey mailing list data is considered highly accurate.  There are survey’s mailed to millions of homes each year, and more and more online surveys are popping up every year.