Industry-Specific Data Mining Tools Emerging
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ComputerWorld has reported that, in an effort to increase marketplace acceptance, vendors are focusing their latest generation data-mining tools on specific applications or industry segments. The reason: "Corporations are finding it difficult to take raw technologies and apply them to their business. They need solutions that can be absorbed faster so they can see the (return on investment) faster," said A. J. Brown, vice president of marketing at DataMind Corp. in Redwood City, Calif.

To hide some of the complexity and broaden the base of users beyond statisticians, vendors are packaging application-specific code along with the mining engines. That makes the systems faster to implement and easier to learn. Applications that vendors are targeting include database marketing and fraud detection. Industries for which tailored packages have been designed include retail, banking and telecommunications.

Because data-mining technology is complex, time-consuming and expensive, getting a return on investment (ROI) -- and even accurate results -- can be a lengthy process. Data-mining tools use advanced techniques in mathematics and artificial intelligence to uncover patterns in data and develop predictive models. Those models are then used to help solve business problems.

The targeted approach is new, and most of the products are new or emerging. Bank of America in San Francisco is evaluating a product geared toward commercial banks. The product line, from HyperParallel, Inc., includes application templates called Solution Frameworks and a mining engine called Discovery.

HyperParallel has templates for the retail industry for functions such as markdown management; for banking for functions such as fee tolerance; and for telecommunications. Eight templates are available now; 15 others will be available by the end of next year, according to the company.

Although Bank of America has a 22-person database marketing department, including eight statisticians, it is still interested in the banking-specific templates. "We will customize anything that Bank of America buys, but a template is a good place to start," said Chris Kelly, vice president and manager of database marketing. Kelly said the templates will cut deployment and training time. "I like the concept a lot," he added.

Kelly already has experience with HyperParallel. This year, he outsourced a project to the company to score the likelihood of each of 6 million customers' leaving the bank. Using a decision-tree type of algorithm called induction, HyperParallel scored customers every couple of months. Depending on customers' profitability, Bank of America can then decide how much to spend to retain them.

Kelly said the bank has made $4 in profit for every $1 it has spent on customer- retention strategies, though he declined to reveal the cost of the program. He said he outsourced the data-mining portion of the project because in-house statisticians didn't have time to do it.

HyperParallel isn't the only data mining vendor developing niches. Both DataMind and Unica Technologies, Inc. in Lincoln, Mass., target database marketing. Magnify, Inc., based in Chicago, concentrates on fraud. Knowledge Discovery One, Inc. in Austin, Texas, focuses on retailers with its Retail Discovery Suite. And SAS Institute, Inc. in Cary, N.C., announced an alliance last month in which it will write interfaces between its upcoming Enterprise Miner and a marketing campaign management tool called ValEx from Exchange Applications, Inc. in Boston.

Fleet Financial Group, Inc., based in Boston, plans to deploy the Enterprise Miner/ValEx combination. The banking and financial services company will complete installation of ValEx in February. It already uses the current- generation SAS tool and is a beta site for Enterprise Miner. "The goal is to build a fully integrated marketing promotion and data-mining and analysis environment," said Randall Grossman, senior vice president of customer data management and analysis.

Using the current SAS tool, Grossman's team builds predictive models and scores customers. They then must import the results into ValEx. When the tools are integrated via application programming interfaces next year, this process will be automated.

Grossman has projected a five-year ROI of 138% for a 70-person staff, data warehouse and tools -- including online analytic processing, mining and campaign management. The company invested $30 million in the project. However, Grossman, who has an academic background in economics, said he is skeptical about mining vendors' claims that these tools are simple enough for nonstatisticians. He said untrained business users might spend lots of money on marketing campaigns based on misleading correlations uncovered through data mining.

"You can get yourself in a lot of trouble," Grossman said. "I really think it is important to understand the underlying models and variables. "

Hill advises clients to evaluate all segments of a mining product -- from the algorithms to user interfaces. "You want to make sure the product handles all phases well," he said. Otherwise, getting an ROI will be a frustrating experience.