Information Technology Reference
In-Depth Information
transponder number
date
time
location
charge
The agency does not reveal the names of the owners of the cars, so it believes it is pro-
tecting their anonymity. However, many people have an account set up so that their
tollbooth payments are automatically charged to their credit cards. If a credit card com-
pany buys these records from the tollbooth agency, it can match the date, time, and
amount of the tollbooth payments with the date, time, and charge on its credit cards
to determine the identity of the person driving a vehicle with a particular transponder
number. Once this has been done, the credit card company can figure out which cus-
tomers are driving the most miles and are likely to purchase new cars more frequently.
It can then sell this information to banks interested in soliciting automobile loan appli-
cations [28].
PRICE CUSTOMIZATION
Retailers are using information gathered about their customers to offer different prices
to different people. You read about this practice earlier in the chapter in the description
of grocery store loyalty cards. Another example: data aggregation firms sell profiles of
shoppers to some online merchants, who use this information to determine who should
be offered a discount and who should be charged full price and offered more expensive
options [55].
A promising new area in data mining is the incorporation of information collected from
social networks. Here are a few examples of how organizations have used social network
analysis to meet their objectives [56]:
.
In ultracompetitive cell phone markets, it's crucial that companies keep their sub-
scribers from defecting to rival firms. Bharti Airtel, India's largest cell phone com-
pany, uses software to analyze phone records and identify “influencers,” those sub-
scribers most likely to be able to persuade their friends and family members to
follow them when they switch carriers. It then offers the influencers special pro-
motions to keep them loyal. How can Bharti Airtel identify influencers from their
phone records? They are the ones whose calls are quickly returned, who call other
people late at night more frequently, and who get more calls on Friday afternoons
when parties are often organized.
.
Police in Richmond, Virginia, monitor Facebook and Twitter messages to determine
where parties are happening. Data-mining software identifies the party locations
mentioned most frequently. By deploying officers more strategically on big party
nights, the department saves about $15,000 on overtime pay, and the community
has seen a big drop in criminal activity (Figure 5.5).
.
Banks are combining data collected from social networks with credit card state-
ments and other information to evaluate the riskiness of loans. For example, some-
one applying for a loan to start a new business may be a bad risk if the proposed
business has no connection with their social network, educational background,
travel history, or previous business dealings.
