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The news broke earlier this year. Target, the American discount retailer, was in the eye of a storm – a controversy involving teenage pregnancy, discount coupons and oddly enough, predictive analytics. Predictive Analytics is a burgeoning field in almost all businesses but lends itself especially well to retail. This is because it relies on Big Data to predict consumer buying patterns and electronic point-of-sales (POS) systems and loyalty programmes in retail stores have simplified data collection to a great extent. What Target did was apply the power of predictive analytics to unearth a potential gold-mine.
Bang On Target
Andrew Pole, a statistician employed by Target, hit upon the idea of identifying pregnant women among Target’s shoppers and sending them coupons and other promotional materials related to maternity. He did this by first identifying pregnant customers from the baby shower gift registry – the American habit of letting guests known what to gift you on is a marketer’s manna from heaven. But this would only let Target get in at the third trimester – they wanted in early. So, they started running statistical tests on POS data and identified items that pregnant women would typically buy a lot of – iron, calcium, vitamins, minerals, shea butter and body creams, etc. Their program would come up with a pregnancy score for each customer based on the quantity of these purchases and Target would have a target (pun unintended) whom they could inundate with diaper discounts, promotions on nutritional supplements, etc. And it worked! Target sent coupons for baby items to a teenage girl whose parents figured out she was pregnant, all thanks to Target’s coupons. Since then, Target has wised up. Their promotions are much subtler; diaper coupons alongside cutlery or apparel promotions. Stealth is the new mantra.
What customers want
Clearly, there are benefits to knowing what your customers need before they know it themselves. It’s the Holy Grail for marketers. But how ethical is this practice? Customers don’t want to be mere puppets to a marketer’s actions, stealthy or otherwise. We like to believe that every small decision we make is our own and not influenced by others. Funnily enough, we have been prey to the subtle manipulations of marketers for years. Store layouts, shelf placements, print promotions – all goad us into making impulsive purchases. Predictive analytics, at least, point us in the right direction. We get what we need and in Target’s case, at good discounts. It may not be ethical in the true sense but it is mutually beneficial as long as consumers are aware of the practice.
An interesting aspect of predictive analytics is that it can be applied to existing customers whose data the store has access to, but it can also employ a self-learning algorithm which can detect new patterns. Customer buying patterns and the resulting segmentation can then be generalized to the larger population using discriminant demographics allowing retailers to better position products and target customers.
Should we be concerned?
The really worrisome part about predictive analytics is security. Personal information about one’s habits, purchases, demographic and financial information should not be stored away in a remote datacenter opening possibilities for a virtual attack. Certainly, some rules and regulations are necessary to ensure that the consumer’s right to privacy and security are protected at the highest level. As the field of predictive analytics grows with improved data storage and computing technology, expect to see new laws dictating how marketers can use consumer data.