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| Tech Update CRM |
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Data mining: Digging user info for gold
Dancing around privacy
By Rachel Konrad
Special to ZDNet
February 9, 2001

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Most data-mining companies get customer information
from the corporate clients that hire them to build and
host their databases for fees that usually start at
about $10,000 per month. The data miners skirt privacy
concerns by keeping the information in-house.
They then crunch the data and send it back to the
client in the form of spreadsheets, graphics, bar
charts and other visual documents. Some data-mining
companies also act as consultants, recommending to
clients how to tweak Web pages for maximum
effectiveness.
Few data-mining companies are willing to discuss
real-world examples of how the craft has boosted sales
or customers. But Usama Fayyad, a former Microsoft
executive, who left the company to create Kirkland,
Wash.-based DigiMine, said he used data mining to help
revamp Microsoft's MSNBC.com Web site and boost
readership.
Fayyad found that a 22 percent slice of MSNBC readers
had nearly identical online behavior, clicking on
exactly the same reports. But these users didn't fit
into any of the company's five reader categories,
which included political news-hounds, sports junkies
and weather buffs. | [an error occurred while processing this directive] | s MSNBC.com Web site and boost
readership.
Fayyad found that a 22 percent slice of MSNBC readers
had nearly identical online behavior, clicking on
exactly the same reports. But these users didn't fit
into any of the company's five reader categories,
which included political news-hounds, sports junkies
and weather buffs.
Fayyad, who holds a doctorate from the University of
Michigan, said his company determined that the glue
holding this mysterious group together was vaguely
scandalous stories similar to those in gossip
tabloids. MSNBC changed its format significantly to
appeal to this large group, and now the home page is
required to have at least one such feature per day.
The research helped turn MSNBC's Living section into
the site's most popular destination, Fayyad said.
"The lesson is that before data mining, they didn't
know what was happening to a quarter of their
database," Fayyad said. "If three or four shelves fall
over in a brick-and-mortar store, the customers won't
walk around them and the clerks will fix them. The
equivalent is happening on the Web, but no one knows
how to fix the bottlenecks."
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