December 20188IN MY OPINIONWe live in a time of data. Data predicts how we eat, shop, communicate, watch certain programming, and even how we vote. Companies take that data and then target specific advertising when we are on social media or searching online predicting that we might buy their items based on past search. We have all experienced this type of marketing on Amazon or Facebook. A well-known cautionary tale on the use of this type of targeting based on predictive analytics happened back in 2012 in the retail industry, and it provides a valuable lesson for sales and marketers in all industries. Target developed an algorithm to predict when a woman was pregnant based on her purchasing behavior--buying more lotion or vitamins for example. With this knowledge, they would then market to those expectant mothers, coupons in the mail for things like cribs and maternity clothes. In theory, this seems like a great idea for effective marketing. As life changes happen, consumer buying habits change and Target could take advantage of this knowledge to send advertising accordingly. However, Target's predictive modeling was almost too good. One father was angered when his teenage daughter was mailed baby-related coupons, and went to a Target store to demand an apology. A Target representative called the father to apologize (twice!) about the situation a few days later. The father replied "I had a talk with my daughter. It turns out there's been some activities in my house I have not been completely aware of. She's due in August. I owe you an apology."The moral in this story is "don't be creepy." Target could have mixed other coupons in with this to avoid the issue Pro-Actively Using Predictive Modeling in InsuranceBy Scott Stevens, Vice President, Underwriting Workers' Compensation, AmTrust Financial
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