Question1: Go to data

Subject:Computer SciencePrice: Bought3

Share With

Question1:

Go to data.gov—a U.S. government–sponsored data portal that has a very large number of data sets on a wide variety of topics ranging from healthcare to edu-cation, climate to public safety. Pick a topic that you are most passionate about. Go through the topic- specific information and explanation provided on the site. Explore the possibilities of downloading the data, and use your favorite data visualization tool to create your own meaningful information and visualizations.

 

Question 2:

Case Study:

Answer the two case questions on page 244 integrating concepts and examples from that case. 

Predicting Customer Buying Patterns. -The Target Story

In early 2012, an infamous story appeared concern-ing Target’s practice of predictive analytics. The story was about a teenage girl who was being sent adver-tising flyers and coupons by Target for the kinds of things that a mother-to-be would buy from a store like Target. The story goes like this: An angry man went into a Target outside of Minneapolis, demanding to talk to a manager: “My daughter got this in the mail!” he said. “She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?” The manager had no idea what the man was talking about. He looked at the mailer. Sure enough, it was addressed to the man’s daughter and contained advertisements for maternity clothing, nursery furniture, and pictures of smiling infants. The manager apologized and then called a few days later to apologize again. On the phone, though, the father was somewhat abashed. “I had a talk with my daughter,” he said. “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”As it turns out, Target figured out a teen girl was pregnant before her father did! Here is how the company did it. Target assigns every customer a Guest ID number (tied to his or her credit card, name, or e-mail address) that becomes a placeholder that keeps a history of everything the person has bought. Target augments these data with any demographic information that it had collected from the customer or had bought from other information sources. Using this information, Target looked at historical buying data for all the females who had signed up for Target baby registries in the past. They analyzed the data from all directions, and soon enough, some useful patterns emerged. For example, lotions and special vitamins were among the products with interesting purchase patterns. Lots of people buy lotion, but what an analyst noticed was that women on the baby registry were buying larger quantities of unscented lotion around the beginning of their second trimester. Another analyst noted that sometime in the first 20 weeks, pregnant women loaded up on supplements like calcium, magnesium, and zinc. Many shoppers purchase soap and cotton balls, but when someone suddenly starts buying lots of scent-free soap and extra-large bags of cotton balls, in addition to hand sanitizers and washcloths, it signals that they could be getting close to their delivery date. In the end, the analysts were able to identify about 25 products that, when analyzed together, allowed them to assign each shopper a “pregnancy prediction” score. More important, they could also estimate a woman’s due date to within a small window, so Target could send coupons timed to very specific stages of her pregnancy. If you look at this practice from a legal perspective, you would conclude that Target did not use any information that violates customer privacy; rather, they used transactional data that almost every other retail chain is collecting and storing (and perhaps analyzing) about their customers. What was disturbing in this scenario was perhaps the targeted concept: pregnancy. Certain events or concepts should be off limits or treated extremely cautiously, such as terminal disease, divorce, and bankruptcy.

 

Questions for Case 4.7

1. What do you think about data mining and its implication for privacy? What is the threshold between discovery of knowledge and infringement of privacy?

2. Did Target go too far? Did it do anything illegal? What do you think Target should have done? What do you think Target should do next (quit these types of practices)?

 

Sources: K. Hill, “How Target Figured Out a Teen Girl Was Pregnant Before Her Father Did,” Forbes, February 16, 2012; R. Nolan, “Behind the Cover Story: How Much Does Target Know?”, February 21, 2012. NYTimes.com