Credit and Collections Issues for Bill-Me Offers (2,137 words)
Marketers have three options to eliminate bad credit risks: (1) modeling customers who pay and those who don't, (2) suppressing names based on past failure to pay, (3) both.
Modeling is the backbone of the credit-card and financial marketing industry, and it is utilized by other marketers as well. Risk-management companies, including Experian, Fair/Isaac and Acxiom can help consumer direct marketers score customer lists according to financial history, but these services are used most heavily by financial services companies that have more at risk with each offer.
Publishers and continuity marketers commonly use internal and third-party credit and demographic data to model the best and worst customers in their house files. However, these marketers usually prospect with response lists, and response-list rental agreements often forbid the use of external models.
So if you're a consumer direct marketer, what can you do to eliminate bad credit risks? First, use the models you've developed to make savvy list selections. Next, when using rental lists, use in-house suppression files to avoid prospecting to anyone who has already failed to pay for introductory offers.
Merge/purge prospect lists against this house file to suppress bad debt.
Another factor to consider is the lists you use. While your list selections can only imperfectly reproduce your models for less risky customers, some lists are risky, period. For example, Sean Buckley, assistant director of credit for Doubleday Direct, suggests proceeding cautiously with hotline lists, as these new customers might not have paid their bills yet to the marketer that is renting their name.
The Credit Index
Another option for improving campaign pay-up is running prospect lists by The Credit Index, a 65-million-record database compiled from the failure-to-pay, frequent-return and fraud files of more than 70 major direct-response marketers. Because the index is a co-op, only members who contribute to it may use it.