Cashing in on customer insight

white paper | 2012

Cashing in on Customer InsightCustomer analytics can help companies increase loyalty,

profitably grow revenue, and outmaneuver the competition

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

Cashing in on Customer InsightCustomer analytics can help companies increase loyalty, profitably grow revenue,

and outmaneuver the competition

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

preferences.3

Customers’ actions and interactions speak volumes. Purchase behaviors, social conversations,

contact center interactions, responses to promotions—these actions and discussions provide unique

insight into customers’ needs and preferences. Unlocking these insights through customer analytics

allows companies to gain the understanding of their customers required to deliver unique customer

experiences. It also helps organizations determine optimal ways to improve customer engagement,

lifetime value, and satisfaction; and take action to make customer-focused improvements.4

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 analyticsFirst, 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.

Executive Overview

Contents

Executive Overview ______ 2

Creating the Full Customer Picture ________ 4

Assembling the Pieces ___ 5

Pinpointing Profitable Customers ______________ 7

Conclusion ______________ 9


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,

companies that use predictive analytics enjoyed a 73 percent higher sales lift than companies that

don’t use these tools.7 Indeed, advanced analytic and BI tools can provide business leaders with a

single version of the truth when it comes to obtaining a full view of each customer.

Third, the strategic use of customer analytics provides companies with myriad opportunities to

improve customer satisfaction and loyalty. More relevant and timely interactions and offers, for exam-

ple, can make customers feel understood and valued. Tracking customer sentiment and responding

appropriately, as well as reaching out to customers before dissatisfaction occurs (e.g., providing alerts

so customers avoid a banking overdraft or mobile-overage fees), can stimulate customer satisfaction,

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

“Analytics can help busi-ness leaders to identify what’s important to differ-ent customers, pinpoint the next best action, and follow through with the appropriate response.”

—Deepak Advani, vice president, business analytics products and solutions, IBM

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

• Identify granular attributes about customers (e.g., life-stage

changes) that marketing and customer service departments

can use to improve communications and offers.

• Integrate social and other unstructured data with traditional

enterprise feedback and transactional information to develop

a multidimensional view of each customer.

• Use predictive analytics and other types of analysis to opti-

mize offer types, timing, and delivery channel, and to forecast

the anticipated customer value generated as a result.

• Leverage customer intelligence to deliver more

targeted communications, which can help

strengthen the customer-company relationship.

• Amp up customer intelligence by adding analytics

and executive dashboards to determine which

marketing campaigns are most effective with certain

customer groups and why.


Creating the Full Customer PictureCustomers 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.

Fortunately, customers divulge a great deal about themselves through their multichannel

interactions with companies—both intentionally and inadvertently. For instance, customers’

responses to email and direct mail offers, online behaviors, and contact center interactions (e.g.,

agent versus interactive voice response [IVR], reasons, and frequency) reveal an abundance of

information about themselves and their attitudes and opinions. Additionally, many customers

publicize their preferences and attitudes about brands and products on Facebook, Twitter, and

other social channels. They also share a great deal about their interests and changes in their life

stages (e.g., tweeting about the birth of a first grandchild).

Using customer analytics to dig deeply into information that customers share through their

interactions in various channels can reveal granular attributes like why they visited a website

or dropped off before completing a transaction. This detailed information can provide business

leaders with fodder for analysis that competitors can’t match, because they don’t have access

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.

“As the sources of unstruc-tured social customer data continue to grow, business leaders armed with the right tools and resources will be able to harvest these sources of customer in-sights to help craft person-alized sales, marketing, and support experiences that lead to improved customer satisfaction and stronger business returns.”

—Erick Brethenoux, director, business analytics and decision management strategy, IBM

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.

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

13%YOY change in lifetimecustomer value

Average response rate

Average opt-out rate

Percentage, n=112

■ Leaders■ Followers

2.3%

7.1%

4.8%

2.6%

3.9%


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 PiecesCompleting the entire customer picture today involves assembling customer insights from multiple

sources. This includes traditional sources like customer surveys, in addition to customer sentiment

and other information that companies can uncover from comments made in social channels.

A recent Harvard Business Review survey of 2,100 companies found that while 66 percent of

respondents are either currently using social media channels or have social media plans in the

works, just 23 percent are using social media analytics, while just 5 percent are using some form

of sentiment analysis.17 These companies are missing tremendous opportunities for learning

about customer needs and preferences that are being shared in social channels.

“To obtain a holistic view of the customer, companies need to do finer-grained customer

segmentation down to a segment of one,” IBM’s Advani says. This includes demographic

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 viewGaining 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,

“Business leaders who have a clearer picture of each customer are better equipped to develop more accurate propen-sity models and execute strategies that have a much higher likelihood of success.”

—Hamit Hamutcu, partner, Peppers & Rogers Group


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-

standing of each customer’s total value across multiple products. Suncorp-Metway executives

now make more informed decisions about which products to promote to what customers.

Suncorp-Metway’s efforts have generated multiple business benefits. Using customer ana-

lytics helped the company to reduce its direct mail and related operating costs by eliminating

duplicate mailings to the same households and eliminating redundant systems. In addition, the

new master data hub helped the company save roughly USD 10 million annually on integra-

tion and associated costs. Further, because the company has a richer view of each customer,

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.

“To obtain a holistic view of the customer, companies need to do finer-grained customer segmentation down to a segment of one.”

—Deepak Advani, vice president, business analytics products and solutions, IBM

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

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

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

■ Best in Class■ Industry Average■ Laggards

Increase in net client value YOY

% of time spentsearching for data

Customerretention

Customersatisfaction

100%

80%

60%

40%

20%

0%

-20%


Pinpointing Profitable CustomersAs 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

with targeted customers. For instance, when a customer calls a contact center, a company can use

speech and predictive analytics against the information in real time—as well as a customer’s histori-

cal information with the company—to determine the likelihood for that customer to defect, and can

then proactively extend a relevant offer or response intended to retain her.

Analyzing customer activityProviding customers with personalized and relevant communications can help foster customer loy-

alty while increasing customer value in two ways. First, customers who feel they’re understood

and appreciated by a company are more willing to continue doing business with that organization,

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

“Companies can use a blend of transaction, demographic, life stage, and other customer data to gain deeper insights into how much value a customer is generating for them today and what their potential future value may be.”

—Hamit Hamutcu, partner, Peppers & Rogers Group


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

in the use of customer analytics.

Savvy companies use a blend of transactional, demographic, life stage, and other customer

data to develop a clearer picture of the real value that a customer is generating for them today

and what their potential future value is expected to be, Peppers & Rogers Group’s Hamutcu

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.

First Tennessee Bank’s use of predictive ana-lytics has delivered a whopping 642 percent ROI, according to Nucleus Research.

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

Source: Accenture Customer Analytics Survey, May 2011

Speed/level of customer activity

Speed of customer return

Sales team management

Individual customer revenue

Determining reasons for losing customer

Customer service performance

Marketing campaign performance/ROI

Customer activity by channel

26%

■ % saying very beneficial

23%

27%

21%

28%

29%

25%

32%


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

set of customers that have a higher propensity to buy. These efforts enabled the retailer to

improve the performance of its email marketing campaigns, increase the productivity of its

email marketing team, and drive higher conversion rates. Meanwhile, the retailer’s customers

are receiving more relevant offers that lead them to feel that the company truly understands

their needs and preferences, resulting in a more satisfied and loyal customer base.

ConclusionThe 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

“Customer analytics can guide business leaders to make faster, smarter, more effective decisions.”

—Erick Brethenoux, director, business analytics and decision management strategy, IBM


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 Lacki, 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 Shayon, Sheila (2012, February 2). Accenture: Boost Loyalty by Avoiding Blind Spots,

brandchannel. 6 Kaur, Priya (2012, March 12). Understanding Real Value of Your Customers Over Their Lifecycle

(CLV), crmnext. 7 Kucera, 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.