Rebate systems are quite important in classical retail. No matter if fixed via customer card, flexible via campaigns or targeted via couponing, rebates are an important controlling instrument for each retail company. In the last years, especially the instrument of couponing has been increasingly refined and adapted. So far, coupons have been distributed more or less targeted via rebate books or magazines. However, today modern platforms such as check-out couponing are becoming more and more popular. Check-out couponing allows an individual coupon generation at the check-out. At this, the coupon is printed at the end of the sales slip depending on the current customer. The coupons animate the customers to return to the store.

This raises the following question: How can the retailer identify whether a customer is a potential couponing customer and on what coupons he will respond? The DMC Contest 2007 has investigated how Data Mining can be applied for effective control of couponing.

Download of task and data:

DMC2007_en.zip

Download of the class matching into the classification file:

DMC2007_realclass.zip

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For solving the task all data mining tools (self developed or other products) are allowed.