I want E-marketing expert. Please answer the three questions
from the article below:

Q1)Which one of the three pillars of relationship marketing is
best illustrated in the article? Explain how you know and be
specific.?

Q2)Which one of the nine important CRM components used for
e-marketing, described as CRM building blocks in the chapter, is
best illustrated in the article? Explain why.?

Q3)Which one of the ten rules for CRM success is best
illustrated in the article? Explain how you know.?

The article below:

There’s a ton of information out there. And businesses are
figuring out how to put it to work.

The experts call this state of affairs big data. The definition
is squishy, but it usually boils down to this: Companies have
access to vastly more information than they used to, it comes from
many more different sources than before, and they can get it almost
as soon as it’s generated.

Big data often gets linked to companies that already deal in
information, like Google, Facebook and Amazon. But businesses in a
slew of industries are putting it front and center in more and more
parts of their operations. They’re gathering huge amounts of
information, often meshing traditional measures like sales with
things like comments on social-media sites and location information
from mobile devices. And they’re scrutinizing it to figure out how
to improve their products, cut costs and keep customers coming
back.

Shippers are using sensors on trucks to find ways to speed up
deliveries. Manufacturers can trawl through thousands of forum
posts to figure out if customers will like a new feature on their
product. Hiring managers study how candidates answer questions to
see if they’d be a good match.

Lots of obstacles remain. Some are technical, but business as
usual also can stand in the way. In most companies, decisions are
still based on HIPPO — the highest paid person’s opinion — and
persuading an executive that data trumps intuition can be a hard
sell.

What follows are several ways that companies are tapping the
power of data to transform their businesses.

HUMAN RESOURCES

Employee benefits — health care in particular — can be
expensive. Some companies are using big data to get a better handle
on it.

Caesars Entertainment Corp., for one, analyzes health-insurance
claim data for its 65,000 employees and their covered family
members. Managers can track thousands of variables about how
employees use medical services, such as the number of
emergency-room visits and whether they choose a generic or
brand-name drug.

“This is about shining a light on what was a very opaque and
acceptable cost of business that an HR leader or a property team
wouldn’t have thought they had any control over,” says Emily
Gaines, Caesars’ senior vice president of compensation, benefits
and HR effectiveness.

For instance, data in 2010 showed that at a company property,
Harrah’s, in Philadelphia only about 11% of emergencies were being
treated at less-expensive urgent-care facilities, versus 34% across
all of Caesars. The Harrah’s team launched a campaign to remind
employees of the high cost of ER visits and provided a list of
alternative facilities. Two years later, 17% of emergencies were
going to urgent care, and the percentage of individuals making
multiple ER visits fell to 30% from 40%.

Overall, since Caesars began tracking ER visits in 2009, 10,000
emergencies companywide have been shifted to less-expensive
alternatives, for a total savings of $4.5 million.

Big data is also changing hiring. Take Catalyst IT Services, a
Baltimore-based technology outsourcing company that assembles teams
for programming jobs. This year, the company will screen more than
10,000 candidates. Not only is traditional recruiting too slow and
cumbersome, the company says, but also the subjective choices of
hiring managers too often result in new employees who aren’t the
best fit.

“You need to be able to build models that help you take that
subjective view away,” says Michael Rosenbaum, Catalyst’s founder
and chief executive.

So, Catalyst asks candidates to fill out an online assessment —
a move that many companies are making these days, most famously
Google. Catalyst uses it to collect thousands of bits of
information about each applicant; in fact, it gets more data from
how they answer than what they answer.

For instance, the assessment might give a problem requiring
calculus to an applicant who isn’t expected to know it. How the
applicant reacts — laboring over an answer; answering quickly and
then returning later; or skipping it entirely — provides lots of
data about how someone will deal with challenges.

Someone who labors over a difficult question might fit an
assignment that requires a methodical approach to problem solving,
while an applicant who takes a more aggressive approach might be
better in another setting.

The power of this approach is that it recognizes people bring
varied skills to the table, and there’s no one-size-fits-all person
for a job. Analyzing millions of data points can show what
attributes candidates have that fit in specific situations —
something human bias can’t do.

For one measure of success, employee turnover at Catalyst is
only about 15% a year, compared with more than 30% for its U.S.
competitors and more than 20% for similar companies overseas.

PRODUCT DEVELOPMENT

Big data can help capture customer preferences and put that
information to work in designing new products. In this area, online
companies are taking the lead.

Zynga Inc., the San Francisco game maker behind FarmVille,
snares 25 terabytes a day from its games — enough to fill 1,000
Blu-ray discs. It uses that data for customer service, quality
assurance and devising what features will show up in the next
generation of games.

For instance, in the original version of FarmVille, animals were
included mainly as decoration. But Zynga’s game analysts found
players were interacting with the animals far more than designers
had expected, moving them around the farm and using in-game
currency to buy them.

So, in FarmVille 2, animals were made much more central. If you
want to make and sell a cake, for instance, you might need a cow
for the milk and a chicken for the eggs.

Even Zynga’s artists use data when designing new features. In
traditional test marketing, a game designer might test different
versions of, say, a polka-dot cow with a focus group. Zynga’s
artists can draw two different versions and put both in the game to
see which is more popular with players.

Of course, real-world manufacturers are also using big data to
gauge customer interest.

As Ford Motor Co. was designing the first subcompact model on
its new global platform — a common set of components that would be
on Ford cars and trucks around the world — it had to decide what
features common in one region to make available in all regions.

One feature it considered was a “three blink” turn indicator
that’s been available on its cars in Europe for years. Unlike the
signals on its vehicles in the U.S., this indicator flashes three
times at the driver’s touch and then shuts off.

A full-scale market-research test was seen as too costly and
time consuming. So, Ford scoured auto-enthusiast websites and owner
forums to see what drivers were saying about turn indicators. Using
text-mining algorithms, researchers culled more than 10,000
mentions and summarized the most relevant comments.

The three-blink indicator was introduced on the new Fiesta in
2010 and is now available on most of Ford’s products. While some
online commenters have complained that they’ve had trouble getting
used to the new feature, it also has lots of defenders.

“At first, it took some getting used to. Now I wouldn’t have it
any other way!!!” wrote one.

“The use of text-mining algorithms was critical in this endeavor
and helped secure a complete picture that would not have been
available using traditional market research,” says Michael
Cavaretta, Ford’s technical leader for predictive analytics and
data mining.

OPERATIONS

For years, companies have been using digital technology to make
their operations more efficient. With the rise of big data, they
can capture much more information from a wealth of new sources as
it happens.

United Parcel Service Inc. has long relied on data to improve
its operations. In 2009, it began installing sensors in its
delivery vehicles that can, among other things, capture the truck’s
speed and location, the number of times it’s placed in reverse and
whether the driver’s seat belt is buckled. Much of the information
is uploaded at the end of the day to a UPS data center and analyzed
overnight.

By combining GPS information and data from fuel-efficiency
sensors installed on more than 46,000 vehicles, UPS in 2011 reduced
fuel consumption by 8.4 million gallons and cut 85 million miles
off its routes.

MARKETING

Marketers have long used data to understand their customers and
target their pitches. Now a superabundance of data means marketers
can aim for much more personalized messages.

Like many hoteliers, U.K.-based InterContinental Hotels Group
PLC for years has gathered details about the 71 million members of
its Priority Club rewards program, such as income levels and
whether they prefer family-style or business-traveler
accommodations.

Several years ago, the company consolidated all its
customer-marketing information into a single data warehouse, which
can pull in information from social-media sites and process queries
much faster than ever before.

Using the system, it launched a new marketing campaign in
January. Where previous campaigns might have on average seven to 15
customized marketing messages, the new campaign has 1,552,
according to Atique Shah, IHG’s vice president of global guest
campaign marketing.

The messages are rolled out in stages to an initial core of 12
customer groups, each of which is defined by 4,000 attributes. One
group, for instance, tends to stay on weekends, redeem reward
points for gift cards and register through IHG marketing partners,
according to Mr. Shah. So, those customers received a marketing
message that lets them know about local events over the
weekend.

The campaign has generated a 35% higher rate of customer
conversions, or acceptances, than a similar campaign last summer,
says Steve Sickel, IHG’s senior vice president for distribution and
relationship marketing.