How Companies Analyze Your Spending And Habits

Two really good news article explain how companies analyze consumers spending and social networking activity. I highly recommend that you read both articles.

The Forbes magazine article, "How Target Figured Out a Teen Girl Was Pregnant Before Her Father Did," summarized very well the problematic behavior of many corporations and retailers. To get a jump on its competitors, Target extensively analyzed -- perhaps better than most retailers -- its customers' purchases and attached undisclosed demographic data to each customer's identification number to mathematically predict what customers might by.

The prediction formulas were so good, Target was able to mathematically deduce from past purchases that this teen girl was pregnant and send coupons to her home -- all before the teen told her parent of the pregnancy:

"What Target discovered fairly quickly is that it creeped people out that the company knew about their pregnancies in advance... So Target got sneakier about sending the coupons. The company can create personalized booklets..."

These personalized coupon books were an attempt to hide the fact that Target knew so much, and disguise that knowledge by presenting both coupons not related to pregnancy with coupons that were related:

"... we learned that some women react badly... Then we started mixing in all these ads for things we knew pregnant women would never buy, so the baby ads looked random... we found out that as long as a pregnant woman thinks she hasn’t been spied on, she’ll use the coupons. She just assumes that everyone else on her block got the same mailer..."

One of my friends called Target's behavior "untethered stupidity" to market pregancy products to a teenager. Yes, that was incredibly stupid, and was likely enabled by its rush to make money. Some of my friends were surprised at the content of the above Forbes article. I wasn't surprised because of the amount of personal information shared:

• Consumers share on social networking websites the items (e.g., products, services, television/cable shows, music) products we like or prefer,
• Banks regularly collect and resell both debit-card and credit-card purchases,
• Consumers share on social networking websites a wide variety of sensitive personal data (e.g., birth date, children's names and ages, list of relatives). The full birth date makes it easy for data brokers and advertisers to distinguish several people with the same name,
• Consumers share product preferences and travel vacation habits through loyalty program memberships,
• State motor vehicle registries regularly sell drivers' data to companies and data brokers. That includes the car, from which marketers can deduce your wealth, favorite color, and when to pitch extended auto warranty service plans,
• Data brokers like Spokeo and Acxiom compile consumers' demographic data from public records and social networking websites, which retailers can purchase,
• Leaky entertainment, quiz, and gaming apps on social networking websites regularly collect consumers sensitive personal data,
• Leaky smartphone apps regularly collect consumers' sensitive personal data, they often shouldn't. The lack of privacy policies with these apps mean the app developers are free to sell the personal data collected.

What might that undisclosed demographic data be? It's pretty easy to deduce or infer:

• Name, address, age from the store loyalty program registration
• Income from any store credit cards, loyalty program registrations, surveys, or average purchase history over time (e.g., wealthy people spend more, less wealthy purchase more with coupons)
• Favorite colors from the colors of clothes purchased
• Left-handed preference from types of products purchased
• Personal preferences from any product comments at the retailer's web site or products "liked" at social networking websites (purchased from data brokers)
• Type of vision from purchases (e.g., non-prescription sunglasses indicate good vision)
• Health issues (e.g., eczema, dry skin, dandruff) from the types of lotions and shampoos purchased
• Health issues (e.g., over-weight) by the size of clothes purchased or from retailers offering pharmacies and in-store clinics
• Durable goods (e.g., dishwasher, washing machine, gas or electric oven) used at home from purchases
• Auto and electronics owned from purchases, either the item or related accessories purchased
• Approximate ages of children by types of toys purchased or from photographs at social networking websites
• Where else you shop, based on GPS coordinates collected from any apps installed on your smartphone, or data purchased from mobile service providers
• Retail stores that use facial recognition cameras can track your shopping patterns (e.g., when where, duration), even when you pay with cash and left your GPS-enabled cell phone at home, and supplement this with demographic data from photos you are tagged in at social networking websites
• Any gaps in the above demographic data can easily be filled by data purchased from data brokers like Acxiom and/or ads run on social networking websites

The New York Times article, "How Companies Learn Your Secrets," includes a more detailed analysis, with how marketers look for "chunks" in consumers' behaviors to predict future purchases:

"This process, in which the brain converts a sequence of actions into an automatic routine, is called “chunking.” There are dozens, if not hundreds, of behavioral chunks we rely on every day. Some are simple: you automatically put toothpaste on your toothbrush before sticking it in your mouth..."

Some chunks are more complex; consider the series of behaviors women will perform to prepare for a pregnancy: purchase different clothes, lotions, and/or personal hygiene items. Now, think more broadly, because everyone's behaviors can be chunked. Not just women. The researchers found:

"... when some customers were going through a major life event, like graduating from college or getting a new job or moving to a new town, their shopping habits became flexible in ways that were both predictable and potential gold mines for retailers. The study found that when someone marries, he or she is more likely to start buying a new type of coffee. When a couple move into a new house, they’re more apt to purchase a different kind of cereal. When they divorce, there’s an increased chance they’ll start buying different brands of beer. Consumers going through major life events often don’t notice, or care, that their shopping habits have shifted, but retailers notice..."

And a baby definitely qualifies as a major life event.

Now, consider your past purchases. Advertisers value that so they can serve up different products at these major life events. Coombine this with your GPS location in the physical world, and it is a marketers dream: to know you shop every Saturday morning and then serve up ads on your smartphone before you arrive at the supermarket; or to serve up childrens toy and food ads before you shop for their birthday parties.

Maybe all of this doesn't bother you, or maybe it does. The bottom line: where you go in the world, what you purchase, and how much you consume are all pretty personal facts. Consumers should have control over when and with whom this personal data gets shared. If you choose to share everything, fine. Some of us feel and act differently.

Comments

[Christine]

The NY Times article is the orginal. Forbes.com seems to be lifting their content from the Times.