Information Technology Reference
In-Depth Information
are available from a variety of sources, including Experian (one of the three largest credit
report companies in the United States). From its database of more than 200 million
consumers, Experian can provide mailing lists of people in a particular geographical
area who meet certain criteria, including new parents, people who have just moved, new
homeowners, renters with estimated incomes greater than $100,000, health enthusiasts,
sports enthusiasts, and “green” consumers.
A good example of direct mail marketing is Target's efforts to reach pregnant
women. Retailers know that the habits of shoppers—where they buy certain goods and
the brands they select—are difficult to change. However, when people graduate from
college or move to a new town or get married, their shopping habits are more malleable.
New parents are particularly open to changes in their shopping habits. For that reason
Target asked its statisticians to find ways to predict which of Target's women customers
were in their second trimester of pregnancy. The company's goal was to use direct mail
offers to get these women into the habit of buying a wide variety of items at Target stores.
Target's statisticians found customers who had set up baby-shower registries at Tar-
get, then looked back in time to discover what products those women had bought when
they were in their second trimester. The analysts found about two dozen predictors that
a woman is three to six months' pregnant. Tip-offs included purchasing large amounts
of unscented lotion, buying extra-large bags of cotton balls, and spending money on
nutritional supplements, such as zinc and magnesium. The statisticians determined that
they could predict with high confidence whether or not a woman was in her second
trimester of pregnancy by examining her purchases of these “predictor” products. For
those women who were predicted to be pregnant, the statisticians showed they could
predict their expected delivery date within a relatively small window of time.
Target used the algorithms developed by its statisticians to mine its extensive data-
bases of customer purchases. The company identified tens of thousands of women who
were probably pregnant and sent them direct mail advertising. The marketing executives
were savvy enough to know that the women receiving these promotions might be upset
if they discovered Target knew they were pregnant. In order not to tip the women off,
Target made sure that the mailings to the women included offers on wineglasses, lawn
mowers, and other unrelated items mixed in with the offers for diapers, baby clothes,
and cribs [53].
MICROTARGETING
Since 2004 direct marketing based on data mining has become part of US presiden-
tial campaigns [54]. In a technique called
microtargeting
, a campaign combines data
about voter registration, voting frequency, and contributions with consumer data and
information available from a geographic information system to gain insights into which
candidate the voter is likely to favor. The campaign then uses direct mailings, email, text
messages, or home visits to encourage likely supporters to vote.
CONNECTING THE DOTS
Data mining can be surprisingly powerful. Suppose a government agency managing
tollbooths were to sell information records of the following form:
