Data defines the model by dint of genetic programming, producing the best decile table.


Re-Modeling the Coupon Redemption Decision
Bruce Ratner, Ph.D.
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This article re-visits the tradtional statistical Modeling the Coupon Redemption Decision [1] by way of using the machine-learning GenIQ approach. For the results of the Re-Modeling the Coupon Redemption Decision, please contact Bruce Ratner.

[1] - Original article abstract and citation:
ABSTRACT - This article develops a model of the consumer's decision to redeem a coupon on a purchase occasion. The redemption decision is a function of four types of variables - coupon characteristics, characteristics of the purchase, brand loyalty, and concurrent promotional conditions. The underlying hypothesis is that consumers attempt to balance their desire for economy with the minimization of shopping time and effort. As coupons involve both costs and benefits, they will be used only when the incremental perceived effort to redeem is relatively low ar.d perceived value is relatively high. A simplified version of this model is tested with scanner panel data for two product categories.

Caroline M. Henderson (1985) ,"Modeling the Coupon Redemption Decision", in NA - Advances in Consumer Research Volume 12, eds. Elizabeth C. Hirschman and Moris B. Holbrook, Provo, UT : Association for Consumer Research, Pages: 138-143. [ direct url ]: http://acrwebsite.org/volumes/6374/volumes/v12/NA-12

For more information about this article, call Bruce Ratner at 516.791.3544 or 1 800 DM STAT-1; or e-mail at br@dmstat1.com.
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