Targeting one buyer--or a million: Page 3

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Data warehousing meets the Web

Two data warehouse veterans have taken an early stab at defining and describing what they claim is the data warehouse reborn: the data Webhouse.

So far, McNamara says the results of the first phase of the project are pretty impressive. Accrue has enabled to determine where customers are coming from and how long they stay on the site, helping company officials see what advertising vehicles draw their most profitable customers. The clickstream tool has also helped create landing pages for people coming in from different ads--the first step toward personalization, he adds.

But it's when you factor in some of the other pieces of the customer data warehouse project that has seen the greatest return. The site, which started off as a wedding registry, was able to determine with E.piphany that its high-end wedding customers were even more seasonal than originally anticipated. So the firm opted to revamp itself as a general gift registry in July 1999 to balance the spring/summer wedding season with a lucrative business during the fall/winter holiday season. Currently, the pieces of's customer data warehouse are separate, but McNamara says integration is the next big step, along with adding more sophisticated personalization capabilities, e-mail campaign management, and real-time recommendations.

A custom approach

The need to marry Web log data with existing ERP, supply chain, and data warehouse systems is so compelling that some companies are doing their own custom integration or turning to enterprise-class data management tools. LLC, a used car marketplace up and running since June 1998, scrapped a clickstream analysis tool in favor of customizing the SAS suite to tap into data sources other than Web logs. The new system now accesses two Oracle databases--one stocked with spec and availability information on cars, the other with e-mail generated by the site--along with advertising information from its DoubleClick ad server. "We need access to those databases to get the full picture," notes Jerry Johannesen, MIS manager for, in Atlanta. has also prioritized integration with back-end systems as a way to leverage one-on-one marketing to its customer base, says Andy Felong, vice president of engineering for the San Francisco-based online health, beauty, and wellness product superstore. Using a beta version of Oracle's new Data Warehouse Builder, a data warehouse lifecycle tool that will be released in March 2000, is able to use one tool to integrate product-oriented ERP data from its Oracle Financials systems with session-oriented data from its Web site. By mining this mix of data, has been able to identify profitable customers and then reach out to them with custom marketing and cross-selling programs. "We're looking for that competitive edge, and we believe by obtaining the information and mining it, we can get it," Felong says.

For Cyberian Outpost Inc., which aims to provide buyers of electronics and computer equipment with a totally personalized shopping experience, a customized, enterprise Webhouse approach was the only way. With the help of consultants including DiaLogos, Outpost built a system that integrates Sagent Inc.'s data mart environment, Broadvision's e-commerce engine, SAS tools for datamining and Rubrix's campaign management software, now owned by Broadvision. Outpost's personalization goals--to essentially present a known customer with a first screen that caters to all of his or her interests--couldn't be accomplished with clickstream tools, says Dan Bachman, director of business intelligence for Outpost, in Kent, Conn. "Most of the clickstream tools read parsed Web logs and report passively on information; there's no standard way to identify unique sessions or important clicks within a session," he explains.

To address that shortcoming, Outpost designed what it calls a front-end observation server as part of its Webhouse architecture, which is based on Windows NT. This essentially captures the unique user sessions and feeds them into the Sagent data marts for analysis, which is performed overnight. The results of that analysis are then fed back into the system to generate the customized Web screens. The next step, Bachman says, is to use the observation server to analyze the clickstream data in real time. "But we have to walk before we can run," he admits.

Ralph Kimball, a veteran data warehouse expert, is also a proponent of creating a real-time or what he calls a "hot response" cache as part of a Webhouse architecture (see diagram, "How to build a Webhouse"). "That way, the data warehouse can continually anticipate questions and provide a whole set of precomputed responses," says Kimball, president of Ralph Kimball Associates Inc., in Boulder Creek, Calif., and co-author of The Data Webhouse Toolkit (see "Data warehousing meets the Web").

Whatever the approach, smart Web businesses know that guesswork no longer cuts it when it comes to catering to customers. In today's wild and wooly Web world, the name of the game is knowing exactly what customers want and when they want it. And that makes all the difference. //

Beth Stackpole is a freelance writer living in Newbury, Mass. She can be reached at

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