Target Predicts Pregnancy with Big Data

Retail stores may know more about you than you think. When you shop at retail establishments these days, you may unwittingly give information to the company that can lead to it knowing more about you than your own family. Such was the case for a Minneapolis father who found out, from Target of all places, that his teenage daughter was pregnant.

After shopping at Target, the girl began receiving mail at her father’s house advertising baby items: diapers, clothing, cribs and other baby-specific products. Her father was incensed at the company’s attempts to “encourage” pregnancy in teens and complained to the management. A few days later, a shamefaced Dad called the manager to apologize; it appeared his daughter actually was pregnant.

This is not an unusual occurrence with today’s computer-assisted data collections on the part of retail stores. Target assigns customers a Guest ID number that is tied to their name, credit card, email address and every other piece of information the store can collect. Using the information on past purchases, Target is able to create a startlingly accurate profile to use in customer-specific advertising.

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In the case of the lucrative baby industry, Target looks at 25 items purchased by shoppers in various sizes to assign a “pregnancy prediction” score. The giant retailer notes that women in their first trimester tend to purchase calcium, magnesium or zinc supplements as well as unscented lotions. From that small piece of information, Target can then look at other purchases to make other predictions about a woman’s pregnancy like her current trimester and even her due date.

However, Target also realizes that sending baby ads to expectant mothers who have not announced their pregnancies can be intrusive. They often mix in random ads for other products to make the pregnancy ads less noticeable. This practice has helped Target earn over $67 billion in retail sales in 2010 at a time when many stores were going bankrupt, proving that other businesses could benefit from this type of data collection.

Featured image courtesy of Flickr user: t_gregorius