Newport News Gets Summarized Intelligence in Seconds with SAS®

In the highly competitive world of catalog retailing, a marketing manager knows the success of her company is directly related to how well the decision-support group helps her get to know each customer.

At Newport News Catalog, a women's apparel retailer based in Virginia, SAS Customer Relationship Management Solutions offer multidimensional analyses that allow decision-support analysts to provide marketing with customer intelligence in seconds rather than months.

Now that's success, says Lisa Coleman, a Newport News systems analyst who supports the retailer's SAS CRM efforts.

"We can create performance reports that look at each season and allow us to see how customers respond from one season to another so that we can target them with the right mailings in the future," Coleman explains. "Being able to know which customers will respond to a catalog mailing lets us target them strategically, which can lead to cost savings and increased sales. We wouldn't have access to that level of intelligence without SAS."

It's Coleman's job, in part, to provide the analytical intelligence that Newport News' marketing team in New York needs to devise smarter customer strategies and maximize profitability. With SAS, Coleman meets those demands with ease.

Newport News built a 350-gigabyte data warehouse with SAS data tables for marketing and merchandising. It stores information relevant to each order, such as customer number, product purchased, style, size and method of payment.

Newport News' CRM program allows marketing to simultaneously view results of separate mailings of the same catalog to compare response rates. "We allow people in marketing to do that by going through a point-and-click environment in which all they have to do is click on a light bulb icon on their toolbar," Coleman explains. "That signs the individual onto our Starfire (Sun Unix box). What's great about SAS is they can pick which media they want to look at and use macrovariables within the Base SAS code to write different macrovariables to get data from the different data tables."

That way, for example, marketing can get a list of all customers from California who have purchased products on at least two different occasions.

"If we didn't have this SAS-enabled GUI (graphical user interface) and marketing wanted a certain report, we'd have to run the same canned program over and over," Coleman says. "We produce a lot of reports that they might want to use over and over, but we also get a lot of ad hoc queries from them – maybe they want to look at everyone who bought bathing suits in 2001 and see what their subsequent purchases were. SAS provides us with the applications-development ability we need to meet our marketers' increasing demands. And you can do it without knowing SQL (structured language query) or SAS software syntax."

Coleman also uses SAS to power a job-scheduling system she created for the marketing and merchandising data. Marketing is more interested how the books and segments are performing; merchandising likes to look at how products and styles are performing. "The base data between the two systems is the same; it's all based on orders," Coleman explains. "I wrote a SAS\AF program that launches at midnight, reads a warehouse driver file and determines which jobs should run within the schedules – about 200 jobs a night all written in Base SAS code, which runs on our Starfire Unix box."

By running all these jobs, the program is summarizing data. If it detects an error, it will consult a SAS data set to contact whomever is on call and it will send them an e-mail. "We can talk to the Starfire from home, and if we need to make any corrections, we can," Coleman says. "At the same time, SAS is great at being able to create summarized data that has analytical meaning."

Decision support at Newport News has come a long way since the days when it stored customers' buying patterns on tape and then later, on its Unix box segmented by customer number. "Now that we have SAS on that box," Coleman says, "everything is segmented by season, and from that we're able to do summarized data sets that we use to present information to the marketing people. Before SAS, that would have been impossible."

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