1. How does a company determine if its data analysis practices are crossing the data privacy line?
2. Do you agree it was a good idea for Target to mix coupons to help ensure customer privacy?

Chapter Five Case: Data Analysis Gone Wrong Can you imagine receiving an ad from Target informing you that your teenage daughter was pregnant? Yes, this actually happened a few years ago when Target sent an unsuspecting father discount cou- pons for cribs and baby clothes for his teenage daughter who had not told anyone she was pregnant. This incident set off a flurry of outrage and privacy concerns over Target's data analysis practices. I bet you are wondering how big data helped analyze customers' purchases to determine preg- nancy. Target analyzed its data using a unique ID linked to a customer's credit card, name, and purchases to look for patterns (e.g., a woman buying prenatal vitamins) to then send them special deals and coupons for baby items. When Target's data analysis system analyzed customer pur- chase data based on 25 products that pregnant women frequently buy, it could assign a pregnancy prediction score to each shopper and estimate her due date so Target could send her relevant cou- pons for various stages of her pregnancy. After massive customer outrage over privacy concerns, Target began mixing customized coupons by offering a coffee maker with a crib or coupons for baby clothes with wine glasses, so someone reviewing the coupons could not determine anything about the customer