A unified platform for analytics that can provide synergistic insights across marketing, sales and customer service is the key to achieving maximum value from customer relationships.

Customer-first. Customer-focused. Customer-
driven. Customer-centric. Customerobsessed.
The words have been bandied
about in the management lexicon in the last few
decades as though each new wave of strategists
were the first to realize that revenue comes …
from customers.

That fact seems self-evident, but what has been
less clear is how to fully capitalize on that resource,
how to keep as much of it as possible away from
the competition, and why attempts to be “customercentric”
have so often fallen short of expectations
– both for customers and for the companies that
hope to profit from them.

Enterprises long ago acknowledged the value
of customer relationship management (CRM) –
mobilizing resources around customer relationships
rather than product groups, and fostering activities
aimed at maximizing customer lifetime value. Ditto
for enterprise resource planning (ERP) systems,
which introduced new efficiencies by streamlining
processes across the organization.

 

In many cases, these operational systems brought
value, but they could only do what they were
designed to do: reduce costs and increase efficiency.
Ultimately, improving operational efficiency is like
squeezing an orange: With the first squeeze, you
get a significant return on investment. The next
time, you get a little less, then less. And when your
competitors are doing the same thing, the best you
can accomplish is parity. Clearly enterprisewide
operational platforms are a blessing, but not by
themselves a panacea. Automation is not insight.

Maybe the answer isn’t squeezing a few more
drops out of the orange, but questioning whether
more orange juice really produces more profit.
Maybe those efficiencies are being gained at the
expense of enterprise-level goals. Maybe all these
optimized processes are delivering a suboptimal
customer experience, because they didn’t adapt to
the changing needs of customers.

And boy, are customers changing. When Time
magazine declared that you and I (and six billion
others) are Person of the Year 2006, the magazine
acknowledged an irrevocable evolution: The new
digital democracy is one where we all expect to star
in our own personalized realities. Consumers have
been transformed. They’re not just lining up to buy
what’s offered; they expect to be valued participants
in the process.

Customers blog their grievances, post their
reviews, eBay their castoffs, publish their creativity
and customize their information streams. The global
media machine showcases each as an individual. So
as Customer of the Year 2007, they might fairly ask,
“Why can’t your business do as much for me?” “Why
are you urging me again to activate that equity line,
when it’s clear I don’t need to borrow right now?”
“Why are you sending a promotion for 50,000-mile
service, when I just bought the car three months
ago?” ”When I called about my cell phone problem,
didn’t you notice my contract was due to expire?”
“Why did you taunt me with offers of a ‘prequalified’
loan, only to reject my application later?”

These missteps would lead any customer to
believe you don’t understand their needs and don’t
even remember them. We all want to be valued,
especially now that we’re on the cover of Time.
We’re the stars now. If a company wants our money,
we want red-carpet treatment.

Empowering Marketing, Sales
and Service With Analytics

To meet these challenges, forward-thinking
organizations have amplified their “return on
automation” by investing in analytical CRM as well.
As the name implies, analytical CRM provides the
understanding and insight an enterprise requires to
confidently make decisions that drive profitability.
Consider the possibilities:

In marketing organizations, analytic insights
enable a company to:

• More effectively retain profitable customers and
  attract others like them, by creating timely and
  tailored marketing programs that reflect each
  customer’s uniqueness and preferences;
• Adjust pricing strategies to counter
  competition, win sales and maximize
  profitability;
• Increase sales per customer by predicting
  which are most likely to buy, based on
  multiple factors, such as life milestones,
  acquisitions, external events and more;
• Get the most from investments in advertising
  and other promotions by understanding the
  media mix that optimizes returns;
• Increase customer satisfaction, loyalty and
  referrals by providing consistent customer
  treatment – a cohesive company image –
  across all touch points; and
• Allocate limited resources – such
  as budget, staff, IT systems, etc.,
  – for greatest advantage.

In sales organizations, analytics
empower sales representatives to:

• Focus their efforts on high-value
  prospects who are most likely
  to buy;
• Shorten sales cycles by making
  more timely and relevant offers,
  based on analysis of demographic,
  geographic, attitudinal and
  behavioral data;
• Uncover new sales opportunities
  by better anticipating customers’
  needs; and
• Monitor changes in behavior that could
  trigger specific actions or customer
  engagements.

In service organizations, analytics make it
possible to:

• Proactively monitor, diagnose and predict
  customer service requirements – instead of
  waiting for breakages or outages to occur
  at the customer’s site;
• Understand how to transform a customer’s
  grievance into a positive experience – or even
  an opportunity to delight that customer with
  appropriate, proactive cross-sell/upsell offers;
  and
• Quickly detect emerging issues and pinpoint
  the root causes of product failure, to save
  valuable weeks in the problem resolution
  cycle.

How Can CRM Initiatives
Live Up to This Potential?

The benefits of analytics are compelling, but
they can be elusive too. Why? Some of the
reasons are cultural. Organizational process and
personnel issues – such as buy-in, departmental
politics, flawed procedures or reward programs,
etc., – hinder the effectiveness of CRM. From a
technology standpoint, however, there are four
key factors at play:

• The inability to assemble a 360-degree view
  of each customer, or for that matter, the
  business;
• Shallow analytics, or analytics applied only to
  specific niche functions;
• A gap between analytics and action, i.e.,
  customer intelligence is created but not used;
  and
• Misalignment of department-level actions and
  enterprise-level goals.

The good news is that these limitations are not
insurmountable, and they can be resolved with
technology that is available today. It doesn’t
even require an IT overhaul. You can start small,
supplementing existing systems, and add capabilities
as the business case warrants. Here are the
four key capabilities that address these limitations
and enable analytical CRM to deliver the benefits
it should.

Create a Unified View of the Customer
Across All Touch Points

The issue. Traditional information systems
that feed into CRM programs usually reflect a
process- and product-oriented view of the business,
and use a host of independent systems on
different platforms, which share information in a
limited way.

Integrated salesforce automation, contact
management, marketing automation and contact
center systems provide new levels of
productivity and information sharing
among front-office departments. These
applications may support a shared,
consistent view of their departmental
activities and customer data across
functions, but they still suffer from
incompleteness. They don’t capture
all the ancillary factors – and interdependencies
among them – that drive
customer understanding and better
business decisions.

The solution. To maximize
ROI, enterprises need a technology
infrastructure that supports a unified
view of the customer, spanning all
touch points and systems.

Does that mean existing investments in
traditional transaction-based systems and
operational CRM systems are obsolete? No.
Those systems just need to be able to share their
information through a data warehousing and
analytic structure that brings the parts into a
unified whole.

Unifying data that resides in a multitude of
silo systems and purchased databases creates
a cohesive body of corporate knowledge.
Customer data can be assembled from every
contact point – call centers, email, person-toperson,
fax, the Web and beyond – to construct
an accurate, consistent view of customers
across all available channels.

The integrated knowledge base is continually
updated, validated, reconciled and managed for
integrity. The knowledge base – “one version of
the truth” – disseminates meaningful analysis,
insights and action across operational units,
customer groups and lines of business to optimize
customer value.

Apply Analytics to Drive
Profitable Customer Relationships

The issue. In a dynamic and often unforgiving
economy, companies need to predict and
manage customer needs, not just react to them.
Simple analytics won’t deliver genuine customer
intelligence: the ability to anticipate customer
needs based on an intimate understanding of that
individual’s attributes and behaviors.

The solution. Beyond query-and-reporting
tools that tell an organization where it has been,
advanced analytics provide insight about where it
is headed.

Predictive modeling optimizes customer
interactions and accurately assesses each
customer’s propensity to buy additional products,
pay their bills, behave fraudulently or defect to
the competition.

Descriptive modeling clarifies important
relationships, such as which customers are most
similar to one another and how they respond.
You can also identify product affinities that show
which items sell well together, across many
variables.

Forecasting accurately estimates future
conditions and helps you prepare for them. You
can use forecasting to predict sales, staffing
levels, inventory requirements and warranty
reserves – and proactively prepare to meet trends
in market demand, financial conditions, operating
costs and more.

Optimization identifies the most effective
combinations of factors (such as price/media mix/
customer/offer/channel) to produce peak results
within known business constraints. You can
optimally allocate all resources to achieve desired
outcomes more profitably and on schedule, based
on overall strategic objectives.

Text mining extracts structure and meaning
from unstructured textual data. By exploring and
modeling large amounts of structured data as well
as text-based data, organizations can uncover
hidden relationships and patterns of information.

Experimental design techniques quantify
the effects of many different factors (such as
color/message/image/component) on outcomes.
Understand which factors are causing success or
failure, not just which factors are correlated with
the outcome.

Each technique delivers a different kind of
insight and can be applied to multiple business
problems. SAS integrates all these techniques
into a unified platform, embeds these techniques
into solutions and makes this analytic power
accessible to nonquantitative users.

Many organizations that have invested in
operational systems count on SAS to make up for
analytic deficiencies. For example, many SAS
customers produce forecasts and predictions using
SAS and feed those back into their supply chain
management, CRM and ERP systems to inject
intelligence at decision points in those systems.

Translate Analytic Insight
Into Effective Action

The issue. Customer intelligence is just an
academic exercise if it isn’t used. Many organizations
don’t have a framework in place to fully
exploit the insights their analytical CRM systems
can deliver. Timely information either isn’t flowing
to front-line staff or into operational systems
to drive more effective actions.

The solution. With an integrated platform,
everybody has access to the customer intelligence
they need to perform their function more
effectively. For example:

• Campaign managers can match customer
  profiles to marketing efforts to make the right
  offer to the customer via the right channel, at
  the right time.
• Marketing analysts can understand customer
  response rates across products and campaigns,
  and optimize campaign ROI within given
  constraints.
• Salespeople can access the platform to
  make informed judgments about customer
  engagements. Does this prospect warrant an
  email, a phone call or an in-person visit? The
  system knows.
• The system can automatically note a change
  in behavior, such as missing a monthly
  deposit into a bank account, to trigger an
  action to contact the customer.

This vision is achievable today with an integrated
platform that gives all these business users access
to analytical insight without requiring them to
become statisticians themselves.

Align Marketing, Sales and Service
With Enterprise-level Goals

The issue. Did a decision drive the organization
closer to its goals or not? The “right” decision
from the 10-foot view might very well be the
wrong decision when viewed from 10,000 feet.

The decision that best benefits my group
might be gained at your expense. The decision
that keeps a marketing campaign under budget
might alienate good customer prospects and
ultimately cost more than it gains. The cutback
that saves millions in inventory costs could be
costing untold more millions in lost revenues,
because delivery is sluggish. The prospects that
provided easy targets for sales might be creating
real headaches for service.

The solution. Informed decisions require
coordinated intelligence across the enterprise.
Forward-thinking organizations are integrating
predictive analytics not only within marketing,
sales and service, but also for performance
management at the enterprise level. For example:

• A leading bank uses SAS to predict which
  customers are going to leave, three to six
  months before it actually happens, and with
  80 to 85 percent accuracy. As a result, the
  bank has reduced customer attrition by 50
  percent, across lines of business.
• A major car maker used SAS to trim warranty
  analysis cycles by 70 percent, reduce
  warranty costs by 34 percent per vehicle,
  and speed early detection of emerging issues
  – saving $2.2 million in the first six months.
• A regional medical center used SAS
  to modify patient care protocols while
  monitoring 50 KPIs across the institution,
  and reduced average patient stay by nearly a
  day without compromising patient care. This
  gain increased bed capacity as much as if the
  hospital had built a new 50- to 100-bed unit.

Summary

Marketing groups were among the first to
embrace predictive analytics, for cross-selling,
campaign management, interaction management,
customer acquisition as well as customer
loyalty programs. Other functional groups
are gradually coming to discover the value of
predictive analytics for identifying unexpected
opportunities and anticipating problems. They
know that if they don’t, they leave money on
the table; money that somebody savvier is ready
to grab.

The real winners are the enterprises that
realize that true customer intelligence is about
more than injecting analytics into discrete
decisions or programs. It’s about synergistic
insight across the organization – a holistic
perspective that transcends functional and
organizational boundaries.

Where ERP and CRM platforms unified
operations across the organization, an enterprise
intelligence platform now unifies customer
knowledge and insight. Analytics can drive
success in each customer-facing area, from
marketing to sales to service – but you gain even
greater value from a platform that can bring all
these areas together.

Take advantage of it. It’s within your reach,
and the Customer of the Year 2007 is waiting