CASE STUDY

The hunt for customer insightCabela’s hits pay dirt with its analytic sandbox. by Cheryl D. Krivda

Cultivating business growth only looks

easy from the perspective of spectacu-

lar 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.

With $2.34 billion in 2007 sales, the com-

pany 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, maga-

zines and a television show—all focused on

helping people enjoy the outdoor lifestyle.

Yet the steady growth of Cabela’s was

no sure shot. Helmed by Cabela, now

chairman, and his brother Jim, vice chair-

man, 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 tech-

nology 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, direc-

tor 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 dataCollecting this data and using it to support

the company’s growth has been a learning

process. Not long ago, Cabela’s was still pri-

marily 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 sys-

tems, the retail system collected relatively

little data from customers at the POS.

Yet Cabela’s knew that building the busi-

ness could be done only with savvy market-

ing, which required enhanced insight into

customer preferences and buying patterns.

Because its operational systems were inca-

pable of supporting sophisticated analytics

processing, in the mid-1990s the Cabela’s

CASE STUDY

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.

Photo

grap

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urt Do

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abela’s

PAGE 1 | Teradata Magazine | September 2008 | ©2008 Teradata Corporation | AR-5715

team built a DB2 warehouse and used SAS

tools to perform analytics.

Over time, this solution became unpro-

ductive. Among other issues, the statisti-

cians 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 ver-

sion 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 build-

ing, 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 con-

struct data that would help you develop an

answer,” explains Wynkoop.

Seek new capabilitiesIn 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 questions.”

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 foun-

dation, then worked with consultants from

Teradata Professional Services to modify the

model to meet the company’s unique needs.

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 nor-

mally reserved for DBAs [database adminis-

trators],” says Wynkoop. “Much of this was

learned through trial and error. Each mem-

ber of the team contributed to our under-

standing. Sharing what we learned amongst

ourselves helped us to most effectively use

Teradata analytics with the SAS tools.”

Building in the sandboxMembers 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 data-

base, 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 compro-

mising the performance and data quality of

the EDW.

Each analyst and statistician has an indi-

vidual account and rights to the sandbox as

well as the ability to view and join to produc-

tion data to reduce replication while enhanc-

ing 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 sys-

tem,” 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-

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

> Founded: 1961

> 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)

> Web site: www.cabelas.com

PAGE 2 | Teradata Magazine | September 2008 | ©2008 Teradata Corporation | AR-5715

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 prelimi-

nary 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 insightsUsing the sandbox and the data warehouse,

Marketing analysts and statisticians have

been quick to find innovative ways to lever-

age the technology. To better understand the

effectiveness of marketing efforts, for exam-

ple, 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 commu-

nication vehicle and investigating how each

medium interrelates with other media. Being

able to perform most of the data prepara-

tions without the help of IT—which is simul-

taneously 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 ware-

house, 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 antici-

pated 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 sys-

tem and SAS analytical tools have helped the

company to be more responsive and agile.” T

Cheryl D. Krivda writes about the intersection

of high technology and business practices.

Database: Teradata Database V2R6.2

Server: 4-node Teradata 5500H Server with a “virtual” sandbox

Users: 350 (200 concurrent)

Data model: Logical—Teradata Retail Logical Data Model (RLDM)Physical—Third normal form

Operating system: Linux

Storage: Total for all systems: 32TB

Teradata utilities: Teradata Tools and Utilities 8.2, Teradata Manager and Priority Scheduler

Tools/applications: Teradata Warehouse Miner and products from SAS

Behind the solution: Cabela’s Inc.

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 several expansions.

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.”

—C.D.K.

CASE STUDYCASE STUDY

PAGE 3 | Teradata Magazine | September 2008 | ©2008 Teradata Corporation | AR-5715