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
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
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.
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?
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.
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 answer.
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