Please read teh case and answer 3 questions:

 

CASE:Applebee's, Travelocity, and Others: Data Mining for Business Decisions.

 

Randall Parman, database architect at restaurant chain

 

Applebee’s International and head of Teradata’s user

 

group, opened Teradata’s annual user conference in

 

Las Vegas with a warning to those who aren’t making the best

 

use of their data. “Data are like gold,” Parman noted. “If you

 

don’t use the gold, you will have someone else who will

 

come along and take the opportunity,” speaking to a room

 

packed with almost 3,900 attendees.

 

Parman drew an analogy to the story about Isaac

 

Newton’s discovery of gravity after he was hit on the head

 

with an apple. “What if Newton had just eaten the apple?” he

 

asked. “What if we failed to use the technology available, or

 

failed to use these insights to take action?” Applebee’s, which

 

has 1,900 casual dining restaurants worldwide and grossed

 

$1.34 billion in revenue last year, has a four-node, 4-terabyte

 

data warehouse system. Although the company has a staff of

 

only three database administrators working with the system,

 

“we have leveraged our information to gain insight into the

 

business,” he said. “Some of those insights were unexpected,

 

coming out of the blue while we were looking in a completely

 

different direction.”

 

For example, Applebee’s had been using the data warehouse

 

to analyze the “back-of-house performance” of restaurants,

 

including how long it took employees to prepare food

 

in the kitchens. “Someone had the unanticipated insight to

 

use back-of-house performance to gauge front-of-house

 

performance,” he said. “From looking at the time the order

 

was placed to when it was paid for by credit card and subtracting

 

preparation meal time, we could figure out how

 

long servers were spending time with customers.” Parman

 

added that the information is being used to help the company

 

improve customer experiences.

 

Applebee’s has also advanced beyond basic business decisions

 

based on data—such as replenishing food supplies according

 

to how much finished product was sold daily—to

 

developing more sophisticated analyses. His department, for

 

example, came up with a “menu optimization quadrant” that

 

looks at how well items are selling so that the company can

 

make better decisions about not only what to order, but

 

about what products to promote.

 

Meanwhile, technology vendors see untapped potential

 

for businesses to spend money on software and hardware

 

that lets them use data to make more sophisticated

 

business decisions. “Companies who operate with the

 

greatest speed and intelligence will win,” says Teradata

 

CEO Michael Koehler.

 

Like many companies, Travelocity.com has lots of unstructured

 

data contained in e-mails from customers, call

 

center representative notes, and other sources that contain

 

critical nuggets of information about how customers feel

 

about the travel site. To offset the inability of business intelligence

 

tools to search for unstructured data, Travelocity has

 

launched a new project to help it mine almost 600,000

 

unstructured comments so that it can better monitor and respond

 

to customer service issues.

 

The online travel site has begun to install new text analytics

 

software that will be used to scour some 40,000 verbatim

 

comments from customer satisfaction surveys, 40,000

 

e-mails from customers, and 500,000 interactions with the

 

call center that result in comments to surface potential customer

 

service issues. “The truth is that it is very laborious

 

and extremely expensive to go through all that verbatim customer

 

feedback to try to extract the information we need to

 

have to make business decisions,” notes Don Hill. Travelocity’s

 

director of customer advocacy.

 

“The text mining capability . . . gives us the ability to go

 

through all that verbatim feedback from customers and extract

 

meaningful information. We get information on the

 

nature of the comments and if the comments are positive

 

or negative.”

 

Travelocity will use text analytics software from Attensity

 

to automatically identify facts, opinions, requests, trends, and

 

trouble spots from the unstructured data. Travelocity will

 

then link that analysis with structured data from its Teradata

 

data warehouse so the company can identify trends. “We get

 

to take unstructured data and put it into structured data so we

 

can track trends over time,” adds Hill. “We can know the frequency

 

of customer comments on issue ‘x’ and if comments

 

on that topic are going up, going down, or staying the same.”

 

Unlike other text analytics technology, which requires

 

manual tagging, sorting, and classifying of terms before

 

analysis of unstructured data, Attensity’s technology has a

 

natural language engine that automatically pulls out important

 

data without a lot of predefining terms, notes Michelle

 

de Haaff, vice president of marketing at the vendor. This allows

 

companies to have an early warning system to tackle

 

issues that need to be addressed, she added.

 

VistaPrint Ltd., an online retailer based in Lexington,

 

Massachusetts, which provides graphic design services and

 

custom-printed products, has boosted its customer conversion

 

rate with Web analytics technology that drills down

 

into the most minute details about the 22,000 transactions it

 

processes daily at 18 Web sites.

 

Like many companies that have invested heavily in online

 

sales, VistaPrint found itself drowning, more than a year

 

ago, in Web log data tracked from its online operations.

 

Analyzing online customer behavior and how a new feature

 

might affect that behavior is important, but the retrieval and

 

analysis of those data were taking hours or even days using

 

an old custom-built application, says Dan Malone, senior

 

manager of business intelligence at VistaPrint.

 

“It wasn’t sustainable, and it wasn’t scalable,” Malone

 

says. “We realized that improving conversion rates by even a

 

few percentage points can have a big impact on the bottom

 

line.” So VistaPrint set out to find a Web analytics package

 

that could test new user interfaces to see whether they could

 

increase conversion rates (the percentage of online visitors

 

who become customers), find out why visitors left the site,

 

and determine the exact point where users were dropping off.

 

The search first identified two vendor camps. One group

 

offered tools that analyzed all available data, without any upfront

 

aggregation. The other offered tools that aggregated

 

everything upfront but required users to foresee all the queries

 

they wanted to run, Malone says. “If you have a question

 

that falls outside the set of questions you aggregated the data

 

for, you have to reprocess the entire data set.”

 

The company finally turned to a third option, selecting

 

the Visual Site application from Visual Sciences Inc. Visual

 

Site uses a sampling method, which means VistaPrint can

 

still query the detailed data. but “it is also fast because you’re

 

getting responses as soon as you ask a question. It queries

 

through 1% of the data you have, and based on that . . . it

 

gives you an answer back. It assumes the rest of the 99% [of

 

the data] looks like that. Because the data has been randomized,

 

that is a valid assumption,” notes Malone.

 

VistaPrint, which has been using the tool for just over a

 

year, runs it alongside the 30–40 new features it tests every

 

three weeks. For example, the company was testing a fourpage

 

path for a user to upload data to be printed on a business

 

card. The test showed that the new upload path had the

 

same conversion rate as the control version. “We were a little

 

disappointed because we put in a lot of time to improve

 

this flow,” he adds.

 

When the company added Visual Site to the operation,

 

it found that although the test version was better than the

 

control in three out of four pages, the last page had a big

 

drop-off rate. “We were able to tell the usability team

 

where the problem was,” Malone says. VistaPrint also reduced

 

the drop-offs from its sign-in page after the Visual

 

Site tool showed that returning customers were using the

 

new customer-registration process and getting an error notice.

 

The company fixed the problem, and “the sign-in rate

 

improved significantly and led to higher conversions,” he

 

says. While Malone concedes that it is hard to measure an

 

exact return on the investment, the company estimates that

 

the tool paid for itself several months after installation.

1.

What are the business benefits of taking the time and

effort required to create and operate data warehouses

 

such as those described in the case? Do you see any

 

disadvantages? Is there any reason that all companies

 

shouldn’t use data warehousing technology?

2.

Applebee’s noted some of the unexpected insights obtained

from analyzing data about “back-of-house” performance.

 

Using your knowledge of how a restaurant

 

works, what other interesting questions would you suggest

 

to the company? Provide several specific examples.

3.

Data mining and warehousing technologies use data

about past events to inform better decision making in

 

the future. Do you believe this stifles innovative thinking,

 

causing companies to become too constrained by

 

the data they are already collecting to think about unexplored

opportunities? Compare and contrast both viewpoints in your answe