When used to make predictions, data can be quite powerful! A common example is the story of the retailer Target’s prediction of a customer’s pregnancy. When the company sent coupons for baby products to a teen, her father complained. However, it turned out that she was indeed pregnant. Such stories can be impressive and concerning. In addition to learning trends and patterns from data, data can lead to new information. In the case of Target and the teen, the store did not just know what the teen bought. Those data suggested more information: her pregnancy. As Eric Siegel writes:
[t]his isn’t a case of mishandling, leaking, or stealing data. Rather, it is the generation of new data, the indirect discovery of unvolunteered truths about people. Organizations predict these powerful insights from existing innocuous data, as if creating them out of thin air.
To understand how predictive analytics work, Siegel provides a wealth of examples and in-depth explanations in Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Understanding how organizations glean information from data and use that information helps us understand marketing and decisionmaking today. It also helps us manage our personal data.
Source: Siegel, Eric. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Hoboken, New Jersey: John Wiley & Sons, 2013.
Image: “Women Grocery Shopping.jpg” by Bill Branson (Photographer), on Wikimedia Commons. Public Domain.