By sending direct mail pieces to a better selection of consumers, Cabela’s increased its response rate by 60%, drawing more shoppers into Cabela’s brick-and-mortar stores throughout the U.S. Using the SAS analytics solution integrated with the Teradata data warehouse, “we were able to target a better selection of customers and offer a better selection of products in the flyers to drive customers into the stores,” notes Corey Bergstrom, director of market research and analysis at the $2.3 billion specialty outdoor retailer.
Cabela’s also is using automated SAS analytics to increase sales on the Internet. The retailer’s “You May Also Need” upsell program increased by 300% last year, Bergstrom reports. Additionally, the automated solution allowed Cabela’s to cut costs by eliminating all personnel working on the “You May Also Need” program. “Previously we had multiple people using a manual process to select these products,” says Bergstrom. “Now it is completely automated.”
In fact, Bergstrom says the SAS/Teradata solution has helped to improve business throughout the Cabela’s enterprise. For example, the company has significantly repurposed a number of full-time employees. “Previously we had six statisticians doing catalog model development and we have been able to shift four to focus on other areas of the company such as retail site selection, inventory control and merchandising. Other areas of the company have been able to take on additional workload without additional resources because we have been able to improve processes and convert manual process to automated processes.” Bergstrom adds: “And we have done all this in the last 12 to 18 months.”
Prior to the integration of SAS and Teradata, data was stored in a SAS data mart and required more of the statisticians’ time bringing together different sources of data. SAS reports that previously statisticians spent one to two weeks per month building the data. The Teradata warehouse brings the data together and creates one source of information in a timely, automated fashion. Data is now ready to be analyzed in seconds versus weeks.
Fast-forwarding process improvement
The flexibility and speed of the SAS/Teradata solution has fast-forwarded Cabela’s business goals. “The business case benefits we wrote down three years ago, when we were initially planning this implementation, are miniscule compared to what we have been able to deliver since then,” says Bergstrom. Cabela’s planned to initially use the solution to assist with marketing functions, then later move on to more enterprise support, “but we have been able to move that along a lot faster than we ever thought we could,” he says.
“We were looking at five years plus when we were putting our plans together,” Bergstrom continues. “It has only been two-and-a-half years and we have already surpassed past the five-year plan. Some of the things we are delivering now were not even on the original list.”
In part, Cabela’s may have an advantage over more traditional retailers because it started as a direct marketer, doing most of its business through catalogs. “In the Direct side you know every customer because you have to ship to them,” says Bergstrom. “Using SAS for the past 10 years we have been able to leverage those analytics to properly market to each customer.”
In 2008, for the first time, Cabela’s brick-and-mortar sales surpassed its Direct (catalog and Internet combined) sales.
Segmenting down to the one-customer level
While other retailers are just beginning to collect and analyze the data to cluster their consumers into demographic and/or geographic segments, Cabela’s is looking at the next level of marketing to individual customers. “We know each customer and their value and we think it will be realistic in the future to deliver one-to-one promotions,” notes Bergstrom. For now, though, the incremental cost of delivering personalized catalogs makes this effort unrealistic.
In the meantime, Cabela’s is continuing to refine and improve its processes to better understand its customers and provide more targeted inventory throughout the stores. For the Internet channel, the retailer is beginning to analyze clickstream patterns of customers and will combine that information with purchase activity, call center purchases, retail purchases and participation in the loyalty program. “SAS has given us one view of the customer that we can leverage in all channels.”
Bergstrom’s advice for other retailers is to recognize that “data is one of the biggest assets companies have. To be successful companies must leverage that data and create business insights out of it. Doing analytics on ‘nice to know’ items is not good business. You must identify the business problems and make actionable changes.”