Big Data Targets

I recently read an article titled “How One Woman Hid Her Pregnancy From Big Data”.  In the article, Janet Vertesi, assistant professor of sociology at Princeton University, attempts to hide her pregnancy from marketers by employing the following basic strategies:

• ensuring her pregnancy wasn’t mentioned anywhere on social media
• only purchasing baby- or pregnancy-related items in cash so nothing could be tracked to her credit card or loyalty cards
• using gift cards, also purchased with cash, for online purchases that were confirmed with a different email address and sent to a storage locker
• browsing the internet with Tor, a software designed to help prevent browsing habits and locations from being collected

Ironically enough, according to Vertesi, she said that her habits flagged her as being a criminal rather than a pregnant woman.

This article might not have caught my eye but I recently finished a book called The Power of Habit by Charles Duhigg. One chapter in the book mentions the work done by statisticians hired by Target to analyze buying habits of pregnant women.  Target wishes to earn the loyalty of these particular consumers and intends to do so by analyzing the buying habits and then sending targeted ads at specific times in the pregnancy.  For example understanding the best time in the pregnancy to send the expectant mother ads or coupons for diapers, strollers, clothes or other baby-related items, when she will be ready for purchasing.

From having discussed this idea of targeted advertising with my friends, based on analysis of our buying habits, it seems that there are two sides to the issue.  Some people really enjoy targeted advertising because it means they get coupons or discounts for the exact items that they are interested in.  And others, like myself, feel slightly creeped out that so much data about me is being divulged, collected and analyzed without my complete consent and awareness.

I realize that targeted ads or customized discounts to match an individual’s preferences may seem harmless and can be beneficial, but it always makes me wonder what else can be done with the data.  Or what else is already happening with the data that I don’t know about.