Cabela's hits pay dirt with its analytic sandbox.
by Cheryl D. Krivda
Cultivating business growth only looks easy from the perspective of spectacular
success. Consider the case of Cabela's Inc. Branded as the "World's Foremost
Outfitter" of hunting, fishing and outdoor gear, Cabela's began nearly 50 years
ago at the kitchen table of founder Dick Cabela. He and his wife sold fishing
flies through classified ads and mimeographed catalogs, developing the
mail-order business into a retail and e-commerce phenomenon.
The Cabela's team includes, from left, Ryan Coldwell, Marketing statistician;
Corey Bergstrom, director of Market Research and Analysis; and Dean Wynkoop,
manager of Data Management for Market Research and Analysis.
With $2.34 billion in 2007 sales, the company is now the largest direct
marketer in its industry and a leading specialty retailer. Its operations
include nearly 30 destination retail stores, a bank, a travel agency, magazines
and a television show—all focused on helping people enjoy the outdoor
Yet the steady growth of Cabela's was no sure shot. Helmed by Cabela, now
chairman, and his brother Jim, vice chairman, the company carefully expanded
its market presence from catalog to retail and the Internet. In doing so, the
enterprise developed new channels and learned how to communicate most
effectively with customers in each one.
By using powerful analytics tools to sort through a huge collection of customer
data, Cabela's has taken new and innovative steps to understand and market to
consumers around the world. At the heart of this technology are the enterprise
data warehouse (EDW) from Teradata and SAS analytics tools. "[Our] current
partnership with Teradata has positioned Cabela's to provide more dynamic
information to more areas of the company," says Corey Bergstrom, director of
Market Research and Analysis. "We feel this expanded partnership will provide
even more flexibility in terms of data availability and, ultimately, insights
that can be leveraged to better take care of our customers."
Tracking down data
Collecting this data and using it to support the company's growth has been a
learning process. Not long ago, Cabela's was still primarily a catalog company
with a few retail showrooms to spotlight featured products. Relevant consumer
data was collected and stored in homegrown customer master data management and
order capture systems that supported call center operations.
To enable Internet sales that began in the late 1990s, the company built a Web
site that utilized logic processes and data from those systems exposed as
XML-based Web services that assisted both channels. As more stores began to
sprout, IT installed a point-of-sale (POS) system to track retail data. Unlike
the call center/Internet systems, the retail system collected relatively little
data from customers at the POS.
Yet Cabela's knew that building the business could be done only with savvy
marketing, which required enhanced insight into customer preferences and buying
patterns. Because its operational systems were incapable of supporting
sophisticated analytics processing, in the mid-1990s the Cabela's team built a
DB2 warehouse and used SAS tools to perform analytics.
Over time, this solution became unproductive. Among other issues, the
statisticians needed access through SAS to the DB2 environment, but it was not
scaled to support such extensive processing. So Cabela's deployed a SAS-based
data mart to handle analytics. The company augmented the sales and customer
data sets with demographic and psychographic data in that SAS data mart
independent from the DB2 data warehouse.
"This gave us three versions of the truth," recalls Dean Wynkoop, manager of
Data Management for Cabela's Market Research and Analysis. "We had the source
systems (one version of the truth) that fed into the DB2 warehouse (a second
version of the truth), which was incomplete because the retail system was never
properly tied to it. Then we had the replicated data mart that supported the
SAS analysis (the third version of the truth)."
Users seeking insight from the data struggled. "We spent a lot of time building
the data instead of actually working with the data," says Ryan Coldwell, a
Cabela's Marketing statistician. The extract, transform and load process into
the SAS data mart was run biweekly, but loading often took as long as two
weeks. "By the time it was done building, the data could be up to four weeks
old, and we'd have to start again," he adds.
In addition to the availability and latency problems, the old system simply
could not provide the insight that Cabela's needed to support its growth. "With
the old data mart, you had to know the problem before you could use the IT
resources to construct data that would help you develop an answer," explains
Seek new capabilities
In 2005, Cabela's began searching for a new data warehouse solution and quickly
chose Teradata. "The Teradata mantra of 'any data, any time' rang true for us,"
says Wynkoop. "We're in a world where we don't know what all of the problems
are. If we could get the full range of the data, we could answer the business
The new data warehouse was launched in June 2007 and fully rolled out by
October to the Marketing team. Cabela's used the Teradata Retail Logical Data
Model as a foundation, then worked with consultants from Teradata Professional
Services to modify the model to meet the company's unique needs.
|Cabela's at a glance
Headquarters: Sidney, Neb.
Mission: Deliver innovation, quality and value in products and
services to people who enjoy the outdoor lifestyle
Market position: Largest mail-order, retail and Internet
outdoor outfitter in the world
Sales: $2.34 billion in 2007
Catalogs mailed annually: 140 million to 120 countries
Retail outlets: Nearly 30 in the U.S. and Canada
Stock symbol: CAB (NYSE)
The data warehouse provides insight throughout the organization. Statisticians
use advanced statistical analyses to help Cabela's understand customer trends
and preferences, retail performance, and even product affinity.
Because so many groups at Cabela's use the data warehouse, it was critical that
no one compromise its performance by submitting overly large or problematic
queries. Cabela's IT staff received training from Teradata Education Services,
then taught champions such as Wynkoop how to use the system. Informal in-house
training was provided to show statisticians how to properly use SAS analytical
tools to perform in-database processing that would collect data efficiently
without degrading processing speed.
"For data residing in the sandbox, we had to learn how to create tables with
proper primary indexes to avoid skewing. We had to learn when to use implicit
versus explicit SQL [structured query language] statements. We also had to
learn how to collect statistics and use column compression—things
normally reserved for DBAs [database administrators]," says Wynkoop. "Much of
this was learned through trial and error. Each member of the team contributed
to our understanding. Sharing what we learned amongst ourselves helped us to
most effectively use Teradata analytics with the SAS tools."
Building in the sandbox
Members of the IT team went a step further. From Cabela's EDW, the team created
a 250GB analytic sandbox for the Marketing group. Segregated within a separate
database, the sandbox is a single collection of data put in place by one or
more informal load events, where Cabela's Marketing analysts and statisticians
can collect data and perform in-depth analyses without compromising the
performance and data quality of the EDW.
Each analyst and statistician has an individual account and rights to the
sandbox as well as the ability to view and join to production data to reduce
replication while enhancing analytics. SAS users can place work tables in the
sandbox and use them to manipulate or transform data. "With the sandbox, we do
all of the heavy lifting with the Teradata system," says Coldwell. "Then we can
bring just what we need into the SAS environment."
Members of the Data Management team frequently use the sandbox as a
"pre-production data warehouse," where they can work with augmented data that
is not ready to be added to the main EDW. They also use the sandbox to perform
preliminary data preparation work, defining data requirements and determining
how to use the data. The sandbox is administered by the Data Management team,
which notifies Marketing users when it becomes full and requires cleanup. IT
also uses workload and system management tools that signal when the sandbox
consumes an inordinate amount of resources.
Unearth valuable insights
Using the sandbox and the data warehouse, Marketing analysts and statisticians
have been quick to find innovative ways to leverage the technology. To better
understand the effectiveness of marketing efforts, for example, the Data
Management team built a small database of retail fliers in the sandbox. By
linking sales data to flier data, the Marketing analysts have begun to
understand which blocks of content perform well, leading to improvements in
overall flier performance.
The team is also using the sandbox to assess the value of the company's
advertising efforts. Conducting a simultaneous campaign with e-mail, catalogs
and retail fliers, analysts are measuring the impact of each communication
vehicle and investigating how each medium interrelates with other media. Being
able to perform most of the data preparations without the help of
IT—which is simultaneously working on other important data warehouse
initiatives—saves time for IT and helps the Marketing team gain the
benefits of the data that much faster.
The technology is utilized to make Cabela's more agile. With the data
warehouse, the company receives each day's sales data by the following morning
and can assess conditions and proposed steps—such as launching an e-mail
campaign—to mitigate problems and boost sales. With the old system,
producing the same information would have taken days.
"With the new data warehouse, we're able to respond to questions in a very
timely manner," says Coldwell. "Let's say we need to have information out the
door this afternoon. We can do that because we have one source of data, and we
can access it very quickly using the Teradata environment."
Going forward, the Data Management team expects the sandbox to grow to meet its
needs. In addition, Cabela's has recently expanded its overall Teradata
solution to enable more extensive analysis of customer behavior and provide
even more precise and personal service to its millions of customers.
"With the Teradata system and SAS, we are asking and answering questions today
about our business strategies such as retail expansion that we never would have
anticipated two years ago, when we started on this road," says Wynkoop. "We're
able to give the business information about where we should put stores, and how
we can improve retail performance. In this way, the Teradata system and SAS
analytical tools have helped the company to be more responsive and agile."
|The sandbox from IT's perspective
To provide business users with a safe analytics processing area, Cabela's Inc.
created a 250GB sandbox for the Marketing group. Initially only 100GB, the
popularity of this space for analytics and data manipulation quickly warranted
Using the sandbox, users can create, drop and delete tables, views and
procedures within the database. IT segmented the sandbox, using authorities to
create role-based access. To prevent conflicts, they worked with the analyst
community to ensure that long-running processes are not submitted during
backups of the data warehouse.
The IT department uses Teradata Priority Scheduler to manage workloads. Jobs
that require extensive processing are automatically shifted to lower-priority
groups if they run too long. Using Teradata Manager, the IT team can monitor
performance of the sandbox processing and ensure that the group is not
overloading the sandbox. Analysts can build solutions that meet their needs
without waiting for the team, which is working to build new areas, such as
inventory, within the data warehouse.
"With the sandbox, users can satisfy their requirements while we concentrate on
getting more data available for the whole company," explains Craig Bruner,
Cabela's enterprise data warehouse architect. "We can help productionalize
those views at a later date and put appropriate controls around them. It's a
great way for analysts to get the data they need while freeing us up to focus
on the bigger picture of providing value to the organization."
|Behind the solution: Cabela's Inc.
Teradata Database V2R6.2
4-node Teradata 5500H Server with a "virtual" sandbox
350 (200 concurrent)
Logical—Teradata Retail Logical Data Model (RLDM)
Physical—Third normal form
Total for all systems: 32TB
Teradata Tools and Utilities 8.2, Teradata Manager and Priority Scheduler
Teradata Warehouse Miner and products from SAS
Cheryl D. Krivda writes about the intersection of high technology and business
Photography by Curt Door/Cabela's
Teradata Magazine-September 2008