Cashing in on customer insight

white paper | 2012

Cashing in on Customer Insight
Customer analytics can help companies increase loyalty,
profitably grow revenue, and outmaneuver the competition

Cashing in on Customer Insight
Customer analytics can help companies increase loyalty, profitably grow revenue,
and outmaneuver the competition

Executive Overview

The New York Times columnist Thomas L. Friedman wrote in a January op-ed for the paper that
“Average is over.”1 Friedman was referring to the idea that average skills no longer enable someone
to earn an average wage, due to heightened global competition. But he may well have been talking
about what it takes to succeed as a business.
Being an “average” company isn’t enough. For companies to succeed in today’s global market,
they have to be exceptional in some way. But it’s become increasingly difficult for most compa-
nies to differentiate themselves based on their products and prices. The best way to stand out
today is by offering a unique customer experience.2 Doing so starts by demonstrating a thorough
understanding of customers and by turning that insight into action to meet their specific needs and Contents
preferences.3 Executive Overview_______ 2
Customers’ actions and interactions speak volumes. Purchase behaviors, social conversations, Creating the Full
contact center interactions, responses to promotions—these actions and discussions provide unique Customer Picture_________ 4
insight into customers’ needs and preferences. Unlocking these insights through customer analytics Assembling the Pieces____ 5
allows companies to gain the understanding of their customers required to deliver unique customer Pinpointing Profitable
experiences. It also helps organizations determine optimal ways to improve customer engagement, Customers_______________ 7
lifetime value, and satisfaction; and take action to make customer-focused improvements.4 Conclusion_______________ 9
With customer analytics—including predictive analytics, social analytics, business intelligence,
and decision management—companies are empowered to improve the customer experience and
maximize business outcomes by being proactive, rather than reactive. Comments made in social
channels about a perceived problem with a checkout tool on a company’s website, for example, can
alert company decision-makers about a potential issue before it hits the contact center.

Four ways to leverage customer analytics
First, by analyzing a mix of structured (e.g., transaction data, customer survey data, demographics)
and unstructured (e.g., social media chatter, contact center notes) customer behavior and feedback
data, decision-makers can gain a much clearer understanding of customer pain points in addi-
tion to their needs and preferences. These insights can translate directly into customer experience
improvements, process improvements, and business benefits.
For instance, analyzing a mix of structured and unstructured data using advanced and social
media analytics can reveal what channels customers prefer to use for interacting with companies
and when they prefer to interact, based on such factors as the circumstances surrounding an inter-
action and the time of day. “Customers tell us a great deal in their different types of interactions with
companies,” says Deepak Advani, vice president, business analytics products and solutions, at IBM.
“The use of analytics and BI for reporting results can help business leaders to identify what’s impor-
tant to different customers, pinpoint the next best action, and follow through with the appropriate
response that resonates with customers.”
Understanding customers’ needs, pain points, and preferences and acting on those insights is
also critical to customer retention, and, thus, to business success. Customer expectations today
are higher than ever, and many companies are struggling to retain customers. A recent survey
by Accenture of 10,000 consumers across 27 countries found that two thirds of respondents (66
percent) switched brand loyalty in 2011 due to dissatisfaction with customer service.5 Customer
analytics provides insight that curbs churn and boosts retention.

©2012 Peppers & Rogers Group. All rights protected and reserved. 2

Second, organizations can use customer analytics to help mine disparate data sources to build
rich customer profiles that reveal cross- and upsell opportunities to marketing, sales, and customer
service operations that may have been overlooked. Retailers can use customer analytics, for exam-
ple, to conduct market-basket analyses to better understand what products customers have and
what they may need. In addition, contact center systems can draw from data to prompt agents
with the relevant information and appropriate actions when cross- or upsell opportunities present
themselves during support interactions. By gaining this deep, holistic customer insight, companies
are better able to increase customer lifetime value.6 According to a recent Aberdeen Group report,
“Analytics can help busi-
companies that use predictive analytics enjoyed a 73 percent higher sales lift than companies that ness leaders to identify
don’t use these tools.7 Indeed, advanced analytic and BI tools can provide business leaders with a what’s important to differ-
single version of the truth when it comes to obtaining a full view of each customer. ent customers, pinpoint
the next best action, and
Third, the strategic use of customer analytics provides companies with myriad opportunities to
follow through with the
improve customer satisfaction and loyalty. More relevant and timely interactions and offers, for exam- appropriate response.”
ple, can make customers feel understood and valued. Tracking customer sentiment and responding —Deepak Advani,
appropriately, as well as reaching out to customers before dissatisfaction occurs (e.g., providing alerts vice president, business
analytics products and
so customers avoid a banking overdraft or mobile-overage fees), can stimulate customer satisfaction, solutions, IBM
reduce churn, and help keep customers loyal. Companies can use predictive analytics and decision
management tools to gain the kind of insights needed to help retain customers.
Fourth, decision-makers can use customer analytics to measure and report on key customer
trends influencing sales, marketing, or customer support strategies. Real-time dashboards and busi-
ness intelligence tools make it possible for business leaders to act quickly and decisively on critical
issues shaping business outcomes. For instance, a decision-maker who sees a sudden downturn in
single satisfaction score for business operations in a particular region can drill down to determine
the root cause, and then take quick action to resolve the issue.
Companies can then use planning and forecasting analysis to ensure budget optimization while
applying predictive analytics to customer data to make the right offer at the right time through the
right channel to the right customers. By delivering more relevant and targeted offers, businesses
can reduce marketing waste, improve customer satisfaction, and drive higher conversion rates.
“Your competitors are after your best customers, regardless of the industry you operate in,” says
Hamit Hamutcu, partner at Peppers & Rogers Group. “Customers have a lot of options, so companies
have to work harder at understanding customers’ needs, behaviors, attitudes, and preferences.”8

Highlights:
Supported by insights from IBM and Peppers & Rogers Group, this white paper will help readers learn how to:

• dentify granular attributes about customers (e.g., life-stage
I • everage customer intelligence to deliver more
L
changes) that marketing and customer service departments targeted communications, which can help
can use to improve communications and offers. strengthen the customer-company relationship.
• ntegrate social and other unstructured data with traditional
I • mp up customer intelligence by adding analytics
A
enterprise feedback and transactional information to develop and executive dashboards to determine which
a multidimensional view of each customer. marketing campaigns are most effective with certain
• se predictive analytics and other types of analysis to opti-
U customer groups and why.
mize offer types, timing, and delivery channel, and to forecast
the anticipated customer value generated as a result.

©2012 Peppers Rogers Group. All rights protected and reserved. 3

Creating the Full Customer Picture
Customers are complex. Each one has different needs, attitudes, preferences, earning power,
and life events, and can’t be defined simply by her most recent purchase or the pages she visited
on a company’s website. A compilation of various attributes helps complete the picture of each
customer. Without the full range of characteristics, each customer picture is incomplete. “As the sources of unstruc-
tured social customer data
Fortunately, customers divulge a great deal about themselves through their multichannel continue to grow, business
interactions with companies—both intentionally and inadvertently. For instance, customers’ leaders armed with the
responses to email and direct mail offers, online behaviors, and contact center interactions (e.g., right tools and resources
will be able to harvest these
agent versus interactive voice response [IVR], reasons, and frequency) reveal an abundance of
sources of customer in-
information about themselves and their attitudes and opinions. Additionally, many customers sights to help craft person-
publicize their preferences and attitudes about brands and products on Facebook, Twitter, and alized sales, marketing, and
other social channels. They also share a great deal about their interests and changes in their life support experiences that
lead to improved customer
stages (e.g., tweeting about the birth of a first grandchild). satisfaction and stronger
Using customer analytics to dig deeply into information that customers share through their business returns.”
interactions in various channels can reveal granular attributes like why they visited a website —Erick Brethenoux,
or dropped off before completing a transaction. This detailed information can provide business director, business analytics
and decision management
leaders with fodder for analysis that competitors can’t match, because they don’t have access strategy, IBM
to the same breadth of data. Analysis of this unique blend of customer attributes can provide
abundant actionable insights like improvements that can be made to self-service technologies
to increase adoption or specific enhancements to product information on a website that can help
improve conversion rates.
Additionally, decision-makers can access that insight quickly by using today’s customer ana-
lytics tools. “It’s now extremely easy for executives in sales, marketing, and service to have
real-time information about what their customers are buying—or not,” Peppers Rogers
Group’s Hamutcu says. As a result, using analytics against these types of customer insights can
make it easier for business leaders to answer critical business questions quickly (e.g., What can
we do to address the churn risk for this particular set of customers? or Which customers will
respond to an offer for X in which channel?).12,13 “All of those questions that took a lot more time
to answer in the past can now be addressed almost instantaneously,” Hamutcu says.

Figure 1: Outperforming the Competition
Best-in-class companies that effectively use predictive analytics typically outperform other companies
in several aspects of marketing, according to a February 2012 report by Aberdeen Group.

YOY change in lifetime 13%
customer value 2.3%

7.1%
Average response rate
4.8%

2.6% ■ Leaders
Average opt-out rate ■ Followers
3.9%

Percentage, n=112

Source: “Divide Conquer: Using Predictive Analytics to Segment, Target, and Optimize Marketing,” Aberdeen Group


Too many companies overlook opportunities for using customer information that’s shared
with them in social, mobile, email, and other channels. According to the 2011 IBM Global Chief
Marketing Officer Study of 1,734 executives, just 26 percent of responding CMOs and their orga-
nizations are tracking blogs, 42 percent are tracking third-party reviews, and 48 percent are
monitoring consumer reviews to help shape marketing strategies.14,15 Companies are prevent-
ing themselves from obtaining more holistic views of their customers if they neglect customer
attitudes and sentiments shared in social channels.16 Companies that blend structured and
unstructured customer data are able to develop richer and fuller customer profiles that can
enable them to build more comprehensive predictive and propensity models that lead to more
successful results, IBM’s Advani says.

Assembling the Pieces
Completing the entire customer picture today involves assembling customer insights from multiple
sources. This includes traditional sources like customer surveys, in addition to customer sentiment “Business leaders who
have a clearer picture of
and other information that companies can uncover from comments made in social channels.
each customer are better
A recent Harvard Business Review survey of 2,100 companies found that while 66 percent of equipped to develop
respondents are either currently using social media channels or have social media plans in the more accurate propen-
works, just 23 percent are using social media analytics, while just 5 percent are using some form sity models and execute
strategies that have a
of sentiment analysis.17 These companies are missing tremendous opportunities for learning
much higher likelihood
about customer needs and preferences that are being shared in social channels. of success.”
“To obtain a holistic view of the customer, companies need to do finer-grained customer —Hamit Hamutcu,
segmentation down to a segment of one,” IBM’s Advani says. This includes demographic partner, Peppers
Rogers Group
and transactional information about individual customers, but it goes much further than this,
according to Advani. To properly understand customer needs, preferences, and motivations,
companies also must analyze customer behaviors across channels. Additionally, the analysis
within each channel should be multidimensional. For example, what behaviors are customers
exhibiting on a company’s website? What did they do during their last visit? How long did they
stay? When did they leave and why?
Of course, companies sometimes find themselves missing vital information about customers
that’s needed to gain a complete view. This can include critical demographic information like the
ages and genders of children in a household or a recent change in earning status for particular
customers. By using customer analytics against existing customer information, decision-makers
can identify customer information gaps and then conduct very targeted and concise surveys or
prompt contact center agents to ask customers specific questions to fill in the blanks, says Erick
Brethenoux, director, business analytics and decision management strategy, IBM.
Blending structured and unstructured customer data, including new information uncovered
by analyses of information gaps, provides decision-makers with incredibly rich data about their
customers. Business leaders who have a clearer picture of each customer are better equipped
to develop more accurate propensity models and execute strategies that have a much higher
likelihood of success, Peppers Rogers Group’s Hamutcu says.

A single customer view
Gaining a complete view of customers includes being able to blend, analyze, and act on cus-
tomer information that is sometimes siloed in separate business divisions and functional areas.
Siloed information had been a challenge for Suncorp-Metway Ltd., a diversified financial ser-
vices company with operations in Australia and New Zealand.
Mergers and acquisitions over the past decade increased its customer base by 200 percent.18
But this decade-long period of growth also led to 23 different source systems for customer data,


making it difficult for it to gain a single view of customers. Suncorp-Metway executives wanted
a single, integrated view of its customers to ensure that its marketing campaigns didn’t result
in internal conflict between its brands or in a duplication of effort, both of which would have a
negative effect on the company’s bottom line.
By creating a master data hub supported by IBM business intelligence, the company reduced
23 million source records into 9 million unique accounts that contain all the data available for
each customer in one place. This single view enabled Suncorp-Metway to gain a deeper under-
“To obtain a holistic view
standing of each customer’s total value across multiple products. Suncorp-Metway executives
of the customer, companies
now make more informed decisions about which products to promote to what customers. need to do finer-grained
Suncorp-Metway’s efforts have generated multiple business benefits. Using customer ana- customer segmentation
lytics helped the company to reduce its direct mail and related operating costs by eliminating down to a segment of one.”

duplicate mailings to the same households and eliminating redundant systems. In addition, the —Deepak Advani,
vice president, business
new master data hub helped the company save roughly USD 10 million annually on integra- analytics products and
tion and associated costs. Further, because the company has a richer view of each customer, solutions, IBM

Suncorp-Metway has been able to significantly increase market share in key product areas with-
out having to increase its marketing spend. “The more information you can collect about your
customers, the more accurate your analytic models will be,” Advani says.
For some business leaders, having extensive customer data can be overwhelming. Although
many decision-makers express growing interest in the use of “Big Data” (or large sets of both
structured and unstructured customer data), some feel intimidated by two factors: the sheer
volume of data coming into the organizations and how to determine which data are relevant.
By using statistical algorithms, executives can determine what data is and isn’t relevant, thus
reducing the pool of potential data sources to the most germane information, says IBM’s
Brethenoux.

Figure 2: Creating a Complete Customer View
Companies that capture, analyze, and then act on a full set of customers’ interactions, including those
from social, the contact center, transactions, and online, outpace their competitors in customer reten-
tion, customer satisfaction, and customer value, according to a recent study by Aberdeen Group.19

360-Degree View Offers Competitive Advantage to Best-in-Class Firms

100%

80%
■ Best in Class
60% ■ Industry Average
■ Laggards
40%

20%

0%

-20%
Customer Customer % of time spent Increase in net
retention satisfaction searching for data client value YOY

Source: Aberdeen Group, “Creating a Complete Customer View: Best Practices in Master Data Management,” May 2011


Pinpointing Profitable Customers
As decision-makers become more experienced using customer analytics, they uncover customer
insights and ways of applying analytics that they previously hadn’t considered. These include fresh
approaches to devising relevant, compelling offers for customers and to determining the most
effective approach for delivering those offers and communicating with customers based on their
behaviors and stated or inferred channel preferences.
Business leaders can also use customer analytics to refine their cross- and upsell execution. For
example, they can more accurately determine what products customers have purchased and the
next logical product to offer a customer based on transaction history, recent web pages visited, and
products purchased by customers with similar traits.
Additionally, decision-makers can draw from a blend of structured and unstructured customer
data to shape personalized sales, marketing, and customer support strategies that truly resonate “Companies can use a
blend of transaction,
with targeted customers. For instance, when a customer calls a contact center, a company can use
demographic, life stage,
speech and predictive analytics against the information in real time—as well as a customer’s histori- and other customer data
cal information with the company—to determine the likelihood for that customer to defect, and can to gain deeper insights
then proactively extend a relevant offer or response intended to retain her. into how much value a
customer is generating
for them today and what
Analyzing customer activity their potential future
Providing customers with personalized and relevant communications can help foster customer loy- value may be.”
alty while increasing customer value in two ways. First, customers who feel they’re understood —Hamit Hamutcu,
partner, Peppers
and appreciated by a company are more willing to continue doing business with that organization, Rogers Group
Peppers Rogers Group’s Hamutcu says. In addition, engaged customers are also more likely to
share the positive experiences they’ve had with a company with friends and associates, thus helping
to generate incremental revenue.
First Tennessee Bank had done an effective job of collecting data. And yet, amid this abundance
of data, it had a scarcity of cohesive, actionable marketing insights.20 Bank officials determined that
they needed a better way to analyze the large volumes of customer data the bank gathers and
to use that information more effectively for decision making. The bank had built a customer data
warehouse and gathered information from sources like online banking records, ATMs, and call cen-
ter interactions. Nonetheless, the bank still had trouble predicting customers’ future behaviors and
making decisions because it lacked effective techniques and tools for analyzing the information.
One area where the bank saw room for improvement was in its marketing department’s com-
munications. Each month the bank sent out a mailing designed to get customers to purchase a bank
product they weren’t using, such as a checking account or a CD. The campaigns were relatively suc-
cessful, even though the bank was working with limited data sets and without the use of automated
statistical tools. But marketing managers believed the campaigns would have higher success rates
if the mailings targeted a broader, more automated analysis of the bank’s customers that included
customer preferences, behaviors, and transactional histories.
Consequently, First Tennessee Bank began using IBM predictive analytics solutions with its cus-
tomer data sources and historical data on the bank’s marketing campaigns. The marketing team
experimented with different models to hone their data modeling skills, with the goal of cross-selling
more of the bank’s products to customers.
By using IBM customer analytics solutions to analyze data related to customer activity and his-
torical marketing campaigns, the bank has reduced its marketing costs, increased net income, and
improved marketing staff productivity. For instance, by analyzing more customer data points, such
as ATM habits, transaction volumes, and call center interactions, and matching this information with
cross-sell opportunities for checking accounts, savings accounts, CDs, and home equity loans, the
bank’s marketing department has increased the conversion rate of its marketing mailings by more


than 3 percent. Additionally, because the bank’s marketers are armed with greater insights about
its customers, they can send better-targeted, more specific offers. As a result, the bank has slashed
its printing, materials, and postage costs by 20 percent. In addition, the marketing team reduced the
amount of time spent on marketing campaigns by 8 percent.
Overall, the bank’s use of IBM predictive analytics has delivered a whopping 642 percent ROI,
based on an analysis conducted by Nucleus Research. Compelling financial returns like these
are a key reason why a growing number of companies like First Tennessee Bank are investing First Tennessee Bank’s
in the use of customer analytics. use of predictive ana-
Savvy companies use a blend of transactional, demographic, life stage, and other customer lytics has delivered a
whopping 642 percent
data to develop a clearer picture of the real value that a customer is generating for them today
ROI, according to
and what their potential future value is expected to be, Peppers Rogers Group’s Hamutcu Nucleus Research.
says. This includes using customer data and analytics to determine which customers are worth
keeping and which ones are a cost-drag on the enterprise.
Business leaders can leverage these insights to help them develop relevant offers and to
design more customized channel experiences for high-value customers. For instance, under-
standing how most valuable or most growable customers use a company’s website and why
they behave the way in which they do (e.g., pages visited, why they leave) during these inter-
actions can help decision-makers to determine the types of functionality and capabilities that
could further improve customer experiences. Such efforts can help companies to engage these
customers more effectively and increase their loyalty and lifetime value, IBM’s Advani says.
Additionally, insights about customer value and channel preferences and behaviors can also
help decision-makers develop strategies for attracting and guiding different customer segments
to specific channels based on that insight. Lower-value customers who call the contact center to
use the IVR for self-service, for example, may be directed to the website for a more comprehen-
sive self-service experience that also costs the company less.

Figure 3: Improving Business Performance
A recent Accenture survey of 800 senior executives at blue-chip companies around the world found that customer analytics have deliv-
ered significant business benefits, including substantial marketing campaign performance ROI and improvements in customer revenue.21

■ % saying very beneficial

Speed/level of customer activity 26%

Speed of customer return 23%

Sales team management 27%

Individual customer revenue 21%

Determining reasons for losing customer 28%

Customer service performance 29%

Marketing campaign performance/ROI 25%

Customer activity by channel 32%

Source: Accenture Customer Analytics Survey, May 2011


Companies can also benefit from using customer analytics to provide offers or perform proactive
outreach that demonstrates that the company is looking out for customers’ best interests. This could
take the form of a reminder, for example, that a product warranty is about to expire or that there
may be a less-expensive service plan that’s better suited for them.
Although such actions by a company may temporarily impact short-term revenues, the cus-
tomer trust that these actions engender will likely lead customers to buy more from the company
in the future and to recommend that company to others, thus generating greater long-term cus-
tomer value, Hamutcu says.
A large retailer IBM works with has used predictive analytics to improve the efficiency and
effectiveness of its email marketing campaigns. The retailer has built propensity models to iden-
tify the right set of customers for a particular offer and focus its email campaigns on a narrower “Customer analytics can
set of customers that have a higher propensity to buy. These efforts enabled the retailer to guide business leaders to
improve the performance of its email marketing campaigns, increase the productivity of its make faster, smarter, more
effective decisions.”
email marketing team, and drive higher conversion rates. Meanwhile, the retailer’s customers
—Erick Brethenoux,
are receiving more relevant offers that lead them to feel that the company truly understands director, business analytics
their needs and preferences, resulting in a more satisfied and loyal customer base. and decision management
strategy, IBM

Conclusion
The amount of customer data now available through an array of channels and sources is stag-
gering. According to Gartner, the world now generates as much information every two days as
it did from the dawn of civilization to the year 2003.
Companies need to gather and act on the wide range of customer data available to them.
Customer analytics can guide business leaders to make faster, smarter, more effective decisions
around specific customer requirements and budding market trends, IBM’s Brethenoux says.
These decision-making capabilities include being able to forecast the amount of investment
that a company should make in a particular customer or group of customers who have similar
traits, based on the amount of potential value those customers are expected to yield in the
future.
Companies’ use of customer analytics often involves tackling a particular business opportu-
nity from a reverse-workflow approach. Business leaders can start by identifying the outcome
that a business unit is attempting to achieve and by assessing the organization’s capabilities for
achieving that outcome. For example, leaders looking to reduce customer churn by 10 percent
can use customer analytics to help identify primary churn triggers and the steps that can be
taken to address those issues. As part of these efforts, decision-makers also must determine the
key inhibitors (e.g., siloed data) that must be removed before the organization can successfully
embark on its customer analytics journey.
Analytics efforts need to be woven into the everyday operations of a business. When cus-
tomer analytics are managed as a stand-alone function, the value delivered to the business
is often much more limited, because it’s likely that the organization’s culture isn’t analytically
driven and doesn’t foster an environment of continuous learning and improvement. However,
companies that are able to work through obstacles like data silos learn from their use of cus-
tomer analytics, and then apply best practices going forward have a far greater likelihood of
achieving consistent success.
An analytically driven organization takes the time to understand individual customers and
uses that information to tailor offers to them. This kind of personalization is critical for compa-
nies looking to differentiate themselves with customers. “You have to use the information that’s
available to make the customer’s experience special,” IBM’s Advani says, “because if you don’t,
your competitors will.” n


About IBM Business Analytics
IBM Business Analytics software delivers actionable insights decision-makers need to achieve
better business performance. IBM offers a comprehensive, unified portfolio of business intel-
ligence, predictive and advanced analytics, financial performance and strategy management,
governance, risk and compliance, and analytic applications.
With IBM software, companies can spot trends, patterns ,and anomalies, compare “what if”
scenarios, predict potential threats and opportunities, identify and manage key business risks,
and plan, budget, and forecast resources. With these deep analytic capabilities our customers
around the world can better understand, anticipate, and shape business outcomes.

For more information please visit www.ibm.com/business-analytics

About Peppers Rogers Group
Peppers Rogers Group is dedicated to helping its clients improve business performance by
acquiring, retaining, and growing profitable customers. As products become commodities and glo-
balization picks up speed, customers have become the scarcest resource in business. They hold the
keys to higher profit today and stronger enterprise value tomorrow. We help clients achieve these
goals by building the right relationships with the right customers over the right channels.
We earn our keep by solving the business problems of our clients. By delivering a superior
1to1 Strategy, we remove the operational and organizational barriers that stand in the way of
profitable customer relationships. We show clients where to focus customer-facing resources to
improve the performance of their marketing, sales, and service initiatives.

For more information please visit www.peppersandrogersgroup.com

About 1to1 Media
1to1® Media is dedicated to helping organizations across the globe realize the greatest value from
their customer base. We provide resources that help senior executives to drive change and make
customer-based initiatives the centerpiece of their growth strategy.
1to1 Media’s custom publications explore the best practices, trends, and developments from
companies that are using customer initiatives to drive bottom-line impact. Backed by Peppers
Rogers Group, the globally recognized leader in customer strategy and relationship marketing,
1to1 Media combines thought leadership, field experience, and editorial expertise to deliver the
content needed by our audience of more than 130,000 decision-makers.

For more information please visit www.1to1media.com


Endnotes
1
Friedman, Thomas L. (2012, January 24). Average is Over, The New York Times.
2
L
acki, Thomas, Ph.D. (2010). Understanding Customer Experience in Retail Banking, Peppers
Rogers Group, EFMA.
3
Peppers, Don (2010). Capitalizing on Customer Analytics, 1to1 In Action Series.
4
Arnott, Grant (2011, May 16). Leveraging return-on-customeróDon Peppers, PowerMarketer.
5
S
hayon, Sheila (2012, February 2). Accenture: Boost Loyalty by Avoiding Blind Spots,
brandchannel.
6
K
aur, Priya (2012, March 12). Understanding Real Value of Your Customers Over Their Lifecycle
(CLV), crmnext.
7
K
ucera, Trip; White, David (2012, February 1). Divide and Conquer: Using Predictive Analytics to
Segment, Target and Optimize Marketing, Aberdeen Group.
8
Hamutcu, Hamit (2011, October 10). The C-Level Executiveís Greatest Asset: Information, Customer
Strategist.
9
Hoffman, Tom (2011, December 28). Hoffman’s Hot Seat: Connecting Predictive Analytics to
Social Media, 1to1 Media.
10
Hoffman, Tom (2011, April 18). Hoffman’s Hot Seat: The Evolution of Customer Analytics, 1to1
Media.
11
IBM (2011, November). BBVA seamlessly monitors and improves its online reputation.
12
Hamutcu, Hamit (2011, September 14). Customer Valuation is a Crucial Step for Businesses,
Peppers Rogers Group.
13
Spoken Communications (2010, October 19). Cost of acquiring a new customer: 6 to 7 times more
than keeping existing.
14
IBM Institute for Business Value (2012). Customer analytics pay off.
15
IBM (2011, October). From Stretched to Strengthened: Insights from the IBM Global CMO Study.
16
Clark, Cynthia (2012, February 20). 6 Steps to Linking Data for Better Customer Insight,
1to1 Magazine.
17
King, Rachel (2012, February 14). IBM VP: Big data, analytics giving way to ‘social economy,’
ZDNet.
18
IBM (2011, March). Case study: Suncorp-Metway Ltd.
19
Ostrow, Peter (2011, May 25). Creating a Complete Customer View: Best Practices in Master Data
Management, Aberdeen Group.
20
IBM (2011, March 25). IBM Business Analytics: First Tennessee Bank, Nucleus Research.
21
Accenture (2011, May). Accenture Customer Analytics Survey.


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