Call me biased, but
I think creative uses for predictive analytics are pretty cool. Target’s
“pregnancy-prediction model”, explained Thursday in a The New York Times
Magazine
article, is a great example. It should inspire
all of us to take a fresh look at our data and consider what more we can
accomplish with a powerful predictive analysis tool (like RI Analytics) and a little bit of creative thinking.
Target’s journey to
predicting pregnancy started with an idea conceived by its marketing
department. The department had previously conducted surveys which indicated
that once a consumer’s shopping habits are ingrained, it can be hard to change
them – except during certain brief periods of a person’s life, like after a
marriage or the birth of a child, where shopping patterns and brand loyalties
often change. The birth of a child represents a new grocery and household
goods list for new parents, as well as the opportunity for Target to sell
things like cribs, rugs, furniture, car seats, and other items that a person or
couple would not usually buy. Because birth records are public information it
was already common practice for companies to send promotional items to new
parents; so, to stay one step ahead of competitors, marketers at Target wanted
to see if there was a way to predict pregnancy during the second trimester.
Target reviewed the
shopping habits of women who had a baby-shower registry as they approached their
due dates. Eventually they were able to identify about 25 different products
that were indicators of pregnancy, including items like unscented lotion,
vitamin supplements, hand sanitizers and washcloths. By treating the purchase
of each item as a variable, they were able to create a model that assigned each
shopper a pregnancy prediction score based on their purchases. This score was
then used to send out relevant coupons and advertisements tailored to each
woman at a specific point in her pregnancy – before other retailers even knew
she was pregnant. Needless to say, sales in Target’s Mom and Baby department
skyrocketed.
This is one way
that a creative use of data, combined with some predictive analytics, yields
some pretty cool results. Target had the data they needed all along –they just
needed the right person to ask the right question.
-Caitlin Garrett, Statistical Analyst at Rapid Insight
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