IBM Software
Business Analytics
Achieving customer loyalty
with customer analytics
Customer Analytics
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Achieving customer loyalty with customer analytics
Contents
2Overview
3Using satisfaction to drive loyalty
4Customer analytics for customer loyalty
5Areas of effectiveness
6IBM Business Analytics solutions for customer loyalty
7Conclusion
Overview
For reasons both traditional and contemporary, achieving
customer loyalty is an essential capability in today’s
fast-moving marketplace. Businesses have long known
that it is more cost-effective to retain a satisfied customer
than to attract a new one. And that a loyal customer is a
strong competitive advantage because of the recurring
potential for additional revenue. But today’s customers
are more empowered, better informed and more likely
to switch to a competitor at a moment’s notice.
For those that are able to build strong customer relationships
in this age of social media and instant information, the
rewards can be substantial. Loyal customers not only
provide you with their valuable business, but often share
their enthusiasm with their peers online.
According to a Forrester Research study, being a Facebook®
fan of the electronics chain store Best Buy® increases the
likelihood of that customer making an actual purchase there
by more than 500 percent. A loyal customer has the potential
to bring greater value to your organization than ever before.
IBM Software
In this white paper, you’ll learn how organizations like yours
are using customer analytics to build and sustain customer
loyalty. Customer analytics helps answer key questions about
who your customers are, what they want and will do next,
and which actions and strategies are most likely to generate
loyalty. It’s a powerful and innovative technology, but still
operates on the traditional business axiom that customer
loyalty begins with customer satisfaction.
Using satisfaction to drive loyalty
According to recent IBM studies of leading companies
around the world, the number one priority for CEOs is
to engage customers as individuals, and the number one
priority for CMOs is to enhance customer loyalty. Their
focus is on getting closer to the customer, and achieving
loyalty through their ability to satisfy those customers.
But in order to satisfy customers, an organization must
first be able to understand, anticipate and fulfill customer
needs and preferences. They must know:
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How to reply to someone through social media.
The potential causes for satisfaction and dissatisfaction.
Why and when customers are likely to leave for
a competitor.
How to accurately measure a customer’s lifetime value.
What actions will prevent at-risk customers from leaving.
How to satisfy and increase the profitability of their
most valuable customers.
How to align their operations so every customer
interaction increases satisfaction.
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In order to differentiate themselves, businesses can no longer
compete purely on product/service quality or price. They must
gain a deep understanding about a wide range of variables that
affect customer satisfaction. Factors such as personalization of
services, preferences for how they would like to be contacted,
the ability to get the right person on the phone to or get
questions or issues resolved quickly and easily, and many others
build the foundation for customer satisfaction. There is an
enormous amount of customer information that must be
tracked, analyzed and acted upon in order to build loyalty and
gain an edge on the competition.
Customer analytics in action: XO Communications
Telecommunications provider XO Communications needed a
way to identify and understand customers who were at risk of
leaving for a competitor, and take action to retain them. Using
IBM customer analytics, XO was able to significantly improve
customer retention and increase profitability. In the first year
after implementing the IBM solution, the company reduced
customer churn by 8 percent. In the second year, customer
churn dropped by 18 percent. It’s estimated that XO achieves
an annual benefit of nearly 4 million dollars due to its customer
analytics solution.
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Achieving customer loyalty with customer analytics
Customer analytics for customer loyalty
Many successful companies now rely on customer analytics
as the means to harness the volumes of customer information
that can affect loyalty and satisfaction. Customer analytics
provides the ability to not only extract critical insights from
that data, but also to embed it within front line customer
interactions, business processes and operational systems.
In this way it helps to align internal operations so the
customer experience is consistently optimized across the
entire enterprise. In addition to answering the critical
questions mentioned above, forward-looking organizations
are using customer analytics to:
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Guide front-line interactions with customers.
Create and execute customer retention strategies.
Prompt people or systems to proactively address customer
satisfaction issues.
Guide product planning to fulfill future customer needs.
Hire and train employees to act upon customer insights
and improve loyalty.
Align their operations to focus on satisfying customers.
Customer analytics in action: PhotoBox
PhotoBox, a European leader in digital photo printing, uses
IBM customer analytics to better understand its customers
and build loyalty by increasing satisfaction. Through improved
targeting and profiling of customers, PhotoBox achieved a
94 percent “satisfied with purchase” rating from customers.
It also substantially increased customer loyalty, with
unsubscribe rates falling to 0.6 percent. In addition to gains
in customer loyalty, IBM customer analytics also helped the
company increase sales by 30 percent in one year, compared
to an increase of less than 10 percent for its competitors over
the same time period.
So what is customer analytics and how does it work? In the
most basic sense, customer analytics is made possible by
combining elements of predictive analytics and business
intelligence software. It uncovers patterns and trends in
customer behavior and sentiment hidden among different
types of customer data such as transactions, demographics,
social media, surveys and interactions. The results of that
analysis are then used to predict future outcomes so businesses
can make smarter decisions and act more effectively. The
results of customer analytics initiatives are then measured
and delivered back to decision-makers through reports,
scorecards and dashboards. Self-learning predictive models
ensure that each new iteration of customer analytics insight
and the business decisions it drives become more accurate
and effective.
IBM Software
Customer analytics provides businesses with the ability to:
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Analyze all data types to gain a 360-degree view of each
individual customer.
Employ advanced algorithms that uncover relevant patterns
and causal relationships that impact customer satisfaction
and loyalty.
Build predictive models that anticipate future outcomes.
Learn from every customer interaction and apply lessons
to future interactions and strategies.
Deploy customer insights to decision-makers and front
line systems.
Optimize marketing budgets by predicting which customer
targets, messages and channels will yield the best results.
Improve sales forecasting and help minimize sales cycles.
Measure and report on marketing performance.
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Anticipating customer needs. More than 30,000 new
products are introduced each year in North America alone.
And today’s consumers expect personalized products and
services to be available when and where they want them.
Customer analytics can help organizations build loyalty by
predicting customer buying behavior and ensuring that desired
products and services are continuously available. By avoiding
stock outages and aligning products, pricing and promotions
with insights from customer analytics, organizations can
maximize satisfaction and minimize negative customer
experiences. They can also fulfill customer preferences
for purchasing channels, such as selecting a product online
then picking it up in person at a storefront.
Areas of effectiveness
Now let’s take a look at some of the critical areas in which
organizations find customer analytics delivers a significant
impact in their ability to improve customer loyalty:
Customer retention. Customer analytics can ensure that
an organization delivers a consistent experience to each
customer that maximizes satisfaction. Conversely, it can also
act as an “early warning system” when customers are
dissatisfied and offer guidance for retaining them. It provides
the ability to reliably predict which customers are likely to
churn and when, and identify the reasons why particular
customers leave. Finally, customer analytics helps determine
the particular offers and retention strategies that will most
likely be successful with individual customers. Throughout
the process, customer analytics provides guidance to front
line staff and systems at the point of customer interaction
to avoid actions that may trigger customer churn, and apply
actions that will improve customer satisfaction and retention.
Customer analytics in action: BBVA
Financial services provider BBVA needed to detect possible
risks to its reputation in social media in order to improve
customer satisfaction. With IBM Social Media Analytics,
BBVA can now listen to voices and opinions on the bank’s
services and measure the effectiveness of publicity campaigns
concerning the amount of mentions, new products, customer
service and corporate news. This helps the bank understand
clients’ and stakeholders’ needs and desires, speeding up
responses and supporting proactive campaigns to improve
customer satisfaction and loyalty.
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Achieving customer loyalty with customer analytics
Customer lifetime value. Customer analytics can help
organizations identify their most valuable customers and
determine if they are worthy of retention efforts and resources
because of the returns they will provide. For instance, it may
not be worth the time and expense to retain a low value
customer. However, another customer may spend little but
have a large sphere of influence in the social media space.
In that case, special considerations can be made to keep that
customer happy so they continue to say positive things about
the company. Over the long term, customer analytics can
calculate the lifetime value of individual customers, and
identify the attributes of the most profitable customers.
Organizations can use this insight to execute customer
interaction strategies that will help maximize customer
lifetime value.
Marketing campaigns. Customer analytics is a particularly
effective tool for microtargeting customers with customized
marketing offers and promotions. When an organization
attempts to cross-sell or up-sell a customer a product or service
they desire, it can enhance satisfaction. But what about those
they do not? Unwanted marketing campaigns and interactions
can erode loyalty by annoying customers or giving them the
impression that the organization doesn’t understand their
needs and preferences. Customer analytics can help determine
which marketing interactions are likely to please individual
customers and which will not.
IBM Business Analytics solutions
for customer loyalty
IBM Business Analytics solutions offer a wide range of
analytical capabilities to help your business improve customer
loyalty with customer analytics. By combining IBM® SPSS
predictive analytics and IBM Cognos business intelligence
technologies, these solutions deliver deep customer insights
that build stronger, more profitable customer relationships.
They reach across your entire enterprise to help you use
customer analytics improve customer interactions, enhance
satisfaction and loyalty, and track performance so you gain
bigger returns for every dollar spent.
IBM SPSS predictive analytics
With more than forty years of analytic expertise, SPSS
predictive analytics solutions can help you align your
organization around the vast amounts of customer information
available from transactions, emails, surveys, social media
and other data sources both inside and outside your company.
You can anticipate customer needs and behaviors and predict
how customers will respond to marketing campaigns, offers,
communication channels, new products and services. SPSS
solutions embed customer insight and optimized decisions
into your operational processes and front-line customer
interactions so you can act with confidence at the point of
impact to maximize customer satisfaction and loyalty.
IBM Cognos business intelligence
IBM Cognos business intelligence and performance
management software provides you with the integrated
dashboards, scorecards, reporting, analysis, and planning
and budgeting capabilities you need to gain and act on
fact-based insights. It lets all relevant stakeholders across
your organization understand what is working and what is
not in your customer analytics initiatives, so you can make
smarter decisions, outperform the competition and ensure
that customers are satisfied and loyal.
IBM Software
IBM Social Media Analytics
IBM Social Media Analytics is an analytics application
designed specifically for social media. It uses sophisticated
software to assess the volume, sentiment and trends in
consumer conversations across a wide range of social
media sources. You can use this information to guide your
organization’s customer loyalty strategies to be more precise,
agile and responsive to consumer demands, allowing you
to target or calibrate marketing campaigns and customer
interactions to grow market share, enhance reputation and
improve customer satisfaction.
Conclusion
The ability to create and sustain customer loyalty is a critical
capability for organizations. Faced with informed and
empowered customers, and massive volumes of readily
available customer data, businesses need a way to align
their staff and operations to ensure customers are satisfied.
IBM solutions for customer loyalty help organizations use
customer analytics to gain actionable insights from customer
data, and deliver those insights to the people, processes and
systems that can improve customer satisfaction and loyalty.
For more information on how IBM solutions can help you
improve customer satisfaction and loyalty, please visit:
ibm.com/software/analytics/rte/an/customer-analytics.
About IBM Business Analytics
IBM Business Analytics software delivers data-driven
insights that help organizations work smarter and outperform
their peers. This comprehensive portfolio includes
solutions for business intelligence, predictive analytics
and decision management, performance management,
and risk management.
Business Analytics solutions enable companies to identify
and visualize trends and patterns in areas, such as customer
analytics, that can have a profound effect on business
performance. They can compare scenarios, anticipate
potential threats and opportunities, better plan, budget and
forecast resources, balance risks against expected returns and
work to meet regulatory requirements. By making analytics
widely available, organizations can align tactical and strategic
decision-making to achieve business goals. For further
information please visit ibm.com/business-analytics.
Request a call
To request a call or to ask a question, go to
ibm.com/business-analytics/contactus. An IBM
representative will respond to your inquiry within
two business days.
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© Copyright IBM Corporation 2013
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Produced in the United States of America
June 2013
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