Datamining poised to go mainstream

With e-commerce and CRM propelling the market forward and Microsoft on the bandwagon, datamining has finally arrived.
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Datamining poised to go mainstream
With e-commerce and CRM propelling the market forward and Microsoft on the bandwagon, datamining has finally arrived.
By Karen Watterson

October 1999

In this article:
AT A GLANCE: Just for Feet
Who's who in datamining
Techniques used in datamining
Datamining: How it's done
It used to be that datamining was limited to high-end database marketing firms and Global 100 firms--the kind whose online transaction processing (OLTP) systems generated millions of rows of data daily. There's always been an aura of mystery, even magic, associated with datamining. It was a science practiced on powerful UNIX systems overseen by unsmiling statisticians and brilliant mathematicians.

Today that's changing. Many Web sites are generating log files and e-commerce transaction files that are eminently mineable. Last month, for instance, online retail giant Amazon.com made headlines with its "purchase circles," based on the fundamental datamining technique of affinity grouping (clustering). When retail sites suggest specific items to customers based on their past purchases, the sites are using a combination of customer relationship management (CRM) and datamining to increase their revenues.


CIO David Meany, Just for Feet Inc.

Datamining is part of a process called knowledge discovery, where the goal is to better understand the organization's data in order to resolve business problems or capitalize on opportunities.

Sizing things up

Consider retail shoe vendor Just for Feet Inc. (www.feet.com) of Birmingham, Ala. The company has approximately 160 superstores, in addition to 170 Athletic Attic, Athletic Lady, and Imperial Sports stores. Each store carries from 3,000 to 6,000 different shoe styles. Multiply the styles by all the different sizes, and you'll start to appreciate what the shoe industry refers to as the "size explosion." And what better way to take advantage of all that data than with a data warehouse/datamining initiative?

AT A GLANCE:

The company: Based in Birmingham, Ala., Just for Feet Inc. has approximately 160 superstores, plus approximately 170 Athletic Attic, Athletic Lady, and Imperial Sports stores. Each store carries between 3,000 and 6,000 different shoe styles.

The problem: Keeping up with rapidly changing shoe styles.

The solution: A 2.4-terabyte data warehouse that currently mines products and inventory. Mining customer data is on the horizon.

The IT infrastructure: Just for Feet used ICL Plc's Fast Track Development Toolkit to generate the schema for an Informix Corp. Dynamic Server release 8.0 database and perform the initial data population. Transaction-level data in Just for Feet's data warehouse is stored in a Sun Microsystems Inc. Enterprise E6500 server.

Each Just for Feet store functions as its own distribution center. With the "in" styles changing so fast, and with regions--even neighborhoods--having different hot styles, it's not hard to realize how important it is for Just for Feet to have the right kind of shoes in stock at the right location. As a result, it made sense for the company to focus its initial datamining efforts on product rather than customer data. "You can be item-centric or customer-centric," says David Meany, CIO, referring to alternative approaches to designing and mining Just for Feet's terabyte-scale data warehouse. But you can't do both at once.

Datamining purists might say that when Just for Feet generates exception reports for its buyers, that's not genuine datamining. But the company's buyers are thrilled with these weekly and monthly reports on sales that allow them to spend more time on the more creative aspects of their jobs--predicting fashion trends and future demand. Meany explains that Just for Feet also does "real" datamining to find answers to issues. For example, the company analyzes distribution practices to see how they impact product sell-through.

The first two phases of the company's multiphase data warehousing/datamining initiative are now in production, built with the help of ICL Plc (www.icl.com), a global IT services company based in London. Just for Feet used ICL's Fast Track Development Toolkit to generate the schema for an Informix Corp. Dynamic Server release 8.0 database and perform the initial data population. Currently, Meany only keeps about a year's worth of transaction-level data in Just for Feet's data warehouse, which is stored in a Sun Microsystems Inc. Enterprise E6500 server. The system maintains aggregate data for 1997 and 1998.

Although the first stages of Just for Feet's implementation have been inventory-focused, plans are already underway to expand the company's analysis capabilities and better leverage the customer component of the data warehouse. Keeping up with the "in" styles is only part of the lure of customer data. Consumers can join the Just for Feet club, with the enticement of special savings. Membership is easy, all you have to do is enter a telephone number and the system does a reverse lookup to determine the address. Is Meany looking forward to mining all of this customer data? You'd better believe it.




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