| Description |
Selects |
Pro's & Con's |
Auto Prescreen Credit Data
Our Auto Prescreen Credit Database allows you to qualify auto dealer prospects by their personal credit attributes. Doing so ensures that you will only invite qualified prospects into the dealership so your sales department can focus on only ideal prospects. |
Credit score
Percentage auto loan paid
Months remaining on lease
First time auto buyer indicator
Bankruptcy eliminator
Recently discharged bankruptcy
Repossession eliminator |
Pro
Actual credit score yields only qualified prospects.
Con
Requires mailer to make a firm-offer-of-credit. |
Modeled Automotive Data
Our Modeled Automotive Data is a predictive product identifying the make and model currently owned by the consumer. Additionally, since current DMV data is used to create our predictive product, we also look at purchase date to determine if the car owner is likely to be considering a new vehicle purchase. This data is successfully used for both new car sales as well as service center traffic. |
Make
Model
Year Build
Purchased Date |
Pro
Ability to select the type of car buyer.
Con
Predictive data has a degree of error. |
Bankruptcy Database
Mailing to people who recently experienced a bankruptcy discharge can also be a great way to increase showroom traffic. For many, the discharge bankruptcy signals a new start and perfect time to for car shopping. Select from months since bankruptcy discharge to suppliment your direct mail campaigns. |
Bankruptcy Type
File Data
Discharge Date |
Pro
Bankruptcy Discharge have a new lease on their car buying ability.
Con
No selects to predict desire. |
Modeled Credit Data (non-firm offer)
For those auto dealerships finding it difficult to make a firm offer of credit, there is modeled credit data. This option does have merit. Some of the modeled data uses auto loan information and personal financial history. This kind of information tells a story about the kind of vehicle the consider purchasing. |
Modeled Credit Score
Modeled Age of auto loan
Modeled Number of Auto loans |
Pro
Predicts the likelihood of a Consumer potentially in the market.
Con
Predictive data has a degree of error. |