MIS 436 Lecture Notes - Lecture 7: Data Mining, Starbucks

• School: Iowa State University
• Department: Management Information Systems
• Course: MIS 436
• Professor: Liu Peng

Document Summary

The prediction of target and target of prediction. Pa application: pregnancy prediction: what"s predicted: which female customers will have a baby in coming months, what"s done about it: market relevant offers for soon-to-ne parents of newborns. Target baby registry: registrants not only disclose they"re pregnant, but they also reveal their due date. Target pulled together training data by merging the baby registry data with other retail customer data, and generate a fairly accurate predictive model. The store can now apply the model to customers who have not register as pregnant. Any and all product categories were analyzed and considered to possible indicators of pregnancy. From the data, analysts at target were able to identify about 25 products that, when analyzed together, allowed them to assign each shopper a pregnancy prediction score. More important, they could also estimate her due date to within a small window, so. Target could send coupons timed to very specific stages of her pregnancy.