Interest and reaction time analysis of credit card offers: Targeted marketing

Interest and reaction time analysis of credit card offers: Targeted marketing

Targeted marketing: the assignment problem

One of the recurrent themes in credit card marketing, and indeed in any direct marketing, is to identify prime prospects. Prime prospects can be identified in many other areas, such as magazine subscriptions, by looking at past history. One can look at their previous subscription behaviour, as well as any additional purchasing they made connected to the magazine. This type of thinking is also valid for credit cards, as long as the issuing bank has the information about the customer. There are several problems, however:

—    Customers are fickle and opt for cards that give the lowest APR

—    Often prospects are not part of one’s own customer group, so that there is no additional information about these individuals

—    Even if an individual is one’s own customer and has defined purchasing history, it is impossible in a simple way to assign membership to one of the psychological segments. If, however, such identification were possible for any individual, then the marketer would be able to present new and powerful offerings to the segment, targeted to the specific interests of that segment

Recently, Moskowitz & Greene (2000) were able to relate membership in a segment to a set of external features about the specific respondent. That is, by acquiring additional information about the respondent from other sources, they were able to construct a decision tree model, allowing them to estimate the likelihood that a new respondent, with the given information, would be a member of one of the two segments. Using a very large sample of new consumers, they were able to show significant increases in the frequency and in the amount of jewellry purchases through the optimisation of the messages, and through the assignment of a given new individual to the appropriate segment (and therefore to the appropriate message). This correct message to the correct individual presents great new opportunities for the credit card industry. It requires a willingness to look at experimentally designed concepts (for optimal communication and segmentation) and a desire to use modelling procedures to assign consumers to these new, non- traditional segments based upon decision trees or other forms of data mining.


Representative APR 391%. Average APR for this type of loans is 391%. Let's say you want to borrow $100 for two week. Lender can charge you $15 for borrowing $100 for two weeks. You will need to return $115 to the lender at the end of 2 weeks. The cost of the $100 loan is a $15 finance charge and an annual percentage rate of 391 percent. If you decide to roll over the loan for another two weeks, lender can charge you another $15. If you roll-over the loan three times, the finance charge would climb to $60 to borrow the $100.

Implications of Non-payment: Some lenders in our network may automatically roll over your existing loan for another two weeks if you don't pay back the loan on time. Fees for renewing the loan range from lender to lender. Most of the time these fees equal the fees you paid to get the initial payday loan. We ask lenders in our network to follow legal and ethical collection practices set by industry associations and government agencies. Non-payment of a payday loan might negatively effect your credit history.

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