Data mining and predictive analytics allow retailers to see into the future: they use collected information to anticipate what their customers want (sometimes even before they know they want it) and custom-tailor their marketing to match. And the practice is only growing more accurate as technology and analytics move forward. A great example of predictive analytics at work is commercial retailing giant, Target. They use big data to calculate which coupons are best at attracting which kinds of customers, and that allows them to, well, “Target” (pun intended) those shoppers accordingly.

To do this, the retailer assigns every customer a unique Guest ID number. The number is linked to their name, credit card number, email address, everything they’ve ever bought from the retailer, and more – a lot more. According to an interview with Target statistician Andrew Pole in the New York Times:

 “If you use a credit card or a coupon, or fill out a survey, or mail in a refund, or call the customer help line, or open an e-mail we’ve sent you or visit our Web site, we’ll record it and link it to your Guest ID… We want to know everything we can.”

Target also links additional demographic information it collects (sometimes by purchasing it from outside firms) to your Guest ID: age; marital status; children; address; commute time; income; whether you are new to the area; what web sites you visit; and what credit cards you use. It might even include subjects to which you have responded in social media. All of this helps Target better aim their ads towards you.

Almost every major retailer today has a predictive analytics department. These are the people who mine the big data, dissect customer profiles and develop more and more efficient ways to market to individuals. And Target’s department is a busy one.

Said Eric Siegel, consultant and chairman of the Predictive Analytics World Conference:

“…Target has always been one of the smartest at this… It’s amazing how much we can figure out about how people think now.”

What Target discovered from their research is that having a baby changes everything – including shopping patterns. Almost all births are recorded in public records, but here’s the rub: targeting customers only after the birth is public knowledge means you compete with everyone else who’s watching the records. You’re essentially behind the eight ball. But predictive analytics can change your position in the market considerably.

Pole explains:

“We knew that if we could identify them (expectant mothers) in their second trimester, there’s a good chance we could capture them for years. As soon as we get them buying diapers from us, they’re going to start buying everything else too.”

Statisticians noted that some purchases seem to foretell pregnancies, well before customers started setting up baby shower gift registries. Buying items like scent-free lotions, as well as vitamin supplements like calcium, magnesium, and zinc, and even jumbo bags of cotton balls are early indicators. The more products on the list purchased, the greater the likelihood a shopper may be pregnant. Pole identified approximately twenty-five products and used them to assign a ‘pregnancy prediction score’ to each Guest ID and get the scoop on the competition.

With this information in hand, Target began to send coupons for baby-related items that matched customers’ pregnancy prediction scores. How successful is the program overall?  Target isn’t saying specifically, but there is one anecdote that gives an indication: this story was shared in journalist Charles Duhigg’s book Ethical Data Mining Applications for Socio-Economic Development:

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 Target manager saw that the mailer indeed bore the name of the man’s daughter, and that it featured smiling infants, plus ads for maternity clothing and nursery furniture. The manager wasn’t aware of the pregnancy prediction program, and apologized to the customer. Presumably after speaking with his supervisors, the manager called a few days later to apologize again.

But it turns out Target knew more than either of the two men:

“I had a talk with my daughter,” said the man. “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August.”

Amazing? Well, it’s really no big surprise if you think about it. Today’s technology allows for massive amounts of data to be collected, stored, and analyzed to create a business “crystal ball”. Amazon uses it to predict what “you may also like”; Google and Yahoo use it to determine which ads appear on your inbox pages; Facebook uses it to decide which ads to incorporate into your feed. Companies (especially retailers) want to see into the future, and get their product in front of customers before the competition catches on.

But you don’t necessarily need a predictive analytics PhD on staff to anticipate your customers’ needs. Even smaller businesses can offer better service (and achieve better ROIs) – it can be as simple as using technology that helps monitor purchases, products, and customer information. Document management (yes document management) systems can remind you of upcoming customer renewal dates, and automate workflows to keep your customer relationships current. There are affordable tools to help you analyze your customer base and target marketing to specific industries or client sizes. All this helps keep you in the know about your customers’ emerging needs and preferences.

5i Solutions customizes their software solutions to your business’s, employees’, and customers’ needs. We can get your documents and data into a digital system that makes searching easy and workflows automated. Organize and analyze your information using metadata that can help you anticipate the future and target your efforts.

5i Solutions. One single, secure point of intake, access, and storage. One singular solution.

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