Chapter 3
Online File W3.1
Using a Data Warehouse to Manage Customer Churn at Sprint
Online File W3.2
A Multidimensional Database
Online File W3.3
More Examples of How Companies Use Data Mining and Warehousing to Support
Marketing
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ONLINE FILE W3.1
IT at Work
Using a Data Warehouse to Manage Customer Churn at Sprint
Stiff competition in the telecommunications market is constantly tempting customers with incentives to switch providers.
That makes churn management, the process of acquiring and
retaining customers, a major challenge for the carriers.
To turn capricious service subscribers into loyal customers,
Sprint’s Global Markets Group relies on a 5-terabyte customer
data warehouse and business intelligence system. The system’s
goals are to increase the amount of business Sprint does with
its business customers and to identify customers who may be
about to defect. Sprint says that churn management is not just
about retaining a customer. It is also about retaining and growing its business. It is easier and less expensive to “up-sell” (sell
new and perhaps more expensive services to existing customers) than it is to acquire new customers.
Sprint’s customer-management effort comes as the
range of services has expanded in recent years to include
local and long-distance voice communications, Internet
access, data communications, and wireless services. Understanding a customer’s needs is critical. Sprint has found that
customers who subscribe to two or more services are much
more likely to stay with Sprint than are customers who use
only one service.
Sprint’s data warehouse contains information from its
customer-billing and customer-service records, augmented
MKT
GLOBAL
with external, publicly available information about business
customers. It is the first time that Sprint has integrated sales
and customer data into one system.
Sprint uses the information to build profiles of its business customers and their service needs. That data is analyzed
using SAS business-intelligence tools, allowing sales and marketing managers to see what additional services they might
sell to customers. Using predictive analysis techniques, Sprint
can identify customers who may be about to move to another
carrier. Warning signs include reduced use of a Sprint service.
That information gives Sprint the chance to correct the problem or offer incentives for users to stay put.
Sprint’s customer churn rate is lower than it was before
the company began using the system. Since the system went
live, it has saved Sprint one million dollars in what the company used to pay outside data-analysis service providers and
database marketing firms. Further, the analysis is done more
quickly—in hours, rather than weeks.
Sources: Compiled from “Managing Customer Churn,” Information
Week (May 14, 2001); and from sprint.com, and sas.com.
For Further Exploration: Why is it more important to retain
customers than to acquire customers? And how does Sprint’s
data warehouse contribute to customer retention?
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A MULTIDIMENSIONAL DATABASE
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Online Figure W3.2.1 A multidimensional database. The front view of the data cube is
shown on the left; the entire view is on the right.
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ONLINE FILE W3.3
MORE EXAMPLES OF HOW COMPANIES USE DATA MINING
AND WAREHOUSING TO SUPPORT MARKETING
• Alamo Rent-a-Car discovered that German tourists liked bigger cars. So now,
when Alamo advertises its rental business in Germany, the ads include information about its larger models.
• Using U.S. census data along with its own internal data, Spalding Sports profiled
thousands of golf courses and pro shops throughout the United States. Promotional materials for each golf course now match the customers’ profiles (such as
upscale golfers versus working-class tourists). They also found that buyers at pro
shops were more interested in technical aspects than buyers at retail stores.
• AT&T and Verizon sift through terabytes of customer phone data to fine-tune
marketing campaigns and determine new discount calling plans.
• A pharmaceutical company analyzes the results of its recent sales force activity to
improve targeting of physicians who should be first contacted; it also determines
which marketing activities will have the greatest impact in the next few months.
The data include competitor market activity as well as information about the
local health care systems. The results are distributed to the sales force via the
Internet, intranets, or a private wide area network.
• A diversified transportation company with a large direct sales force applied data
mining to identifying the best prospects for its services. Using data mining to analyze its own customer experience, this company can build a unique segmentation
identifying the attributes of high-value prospects. Applying this segmentation to
a general business database, such as those provided by Dun & Bradstreet, can
yield a prioritized list of prospects by region.
• A large consumer packaged-goods company applies data mining to improve its
sales process to retailers. Data from consumer panels, shipments, and competitors’
activity are examined to understand the reasons for brand and store switching.
Through this analysis, the manufacturer can select promotional strategies that
best reach its target customer segments.