How
Well Do Your Customers Treat You?
By John
Wookey, Oracle Corp.
A new idea has emerged to predict customer retention. Instead of
measuring how well businesses are treating their customers, businesses are
starting to measure how well customers are treating them.
When it comes to understanding and servicing their customers, many
businesses could be sitting on a gold mine. While investing in costly
surveys and focus groups to measure customer satisfaction, they ignore a
wealth of customer information, streaming in daily from multiple channels.
Companies strive to answer every e-mail, phone call and online query from
clients, but never actually examine the wealth of collective customer
feedback right in front of them about emerging market trends, often-cited
problems or product preferences. If these raw information was understood
as useable intelligence and shared across the enterprise, it would be
worth its weight in gold.
For businesses that want to achieve or increase profitability, gaining
a deeper understanding of customer needs, interests and concerns makes
good business sense. We all know the oft-cited statistic that it is five
to seven times more expensive to acquire a new customer than to retain an
old one. In terms of strategic value, the installed customer base is a
repository of knowledge, which is of immeasurable service to product
development, marketing and sales, financial planners and support
organizations. Moreover, in today's business climate, as new business
opportunities grow scarcer and harder to land, many firms recognize that
their survival depends on keeping existing customers satisfied and
identifying cross-sell and upsell opportunities. In fact, many companies
are rolling out services designed specifically to upsell and cross-sell to
their install base.
One mistake these companies do make, however, is to presume they know
what their customers expect and want based on unreliable surveys and
intuition. How can an organization measure customer wants, needs and
satisfaction more reliably?
Traditional methods, such as customer satisfaction surveys, rarely
produce the hard data or insights companies need to pinpoint problem areas
and affect change. Surveys are broad-based, multiple-choice questionnaires
that can be completed quickly. Unless extremely dissatisfied with the
service, most customers will answer positively.
The chief flaw of the survey is the emphasis on high scores. When
surveys are the barometer of customer satisfaction and are scrutinized at
the highest management levels, they become like self-fulfilling prophecies
-- companies obtain the answers they want. An extreme example of this is
tasking a field sales force to audit its own accounts, and then tying the
results to an incentive. With both their livelihood and reputations at
stake, sales representatives seek out friendly sources, while avoiding
those with legitimate complaints. This is not an egregious practice - it's
human nature. As the seventeenth-century French writer Fran'ois, Duc De
La Rochefoucauld noted, "Few people have the wisdom to prefer the
criticism that would do them good, to the praise that deceives them."
For companies that put stock in surveys, the findings can be confusing
or even misleading. High marks do not necessarily translate into future
sales or customer retention. According to research by Bain & Company's
Loyalty/Retention practice, 60 to 80 percent of customers who defected to
a competitor gave "satisfied" to "very satisfied"
ratings to the previous vendor. In national dealership surveys, it is not
uncommon for a car manufacturer to receive high approval ratings from nine
out of 10 customers, while the repurchase rate remains below 50%.1
Owing to this reality gap, a new idea has emerged to predict customer
retention. Instead of measuring how well businesses are treating their
customers, businesses are starting to measure how well customers are
treating them. The rationale is that if a customer is responsive to a
company, it is a far more accurate gauge of customer satisfaction than a
potentially misleading focus group or a survey.
This new paradigm requires a change in thinking. Organizations must
think about ways to measure how customers are treating them, not
vice-versa. To accomplish that, companies must be able to analyze customer
data and feedback in their myriad forms and locations throughout the
organization. Learning from customers also requires a change in business
processes and systems. While customer relationship management (CRM)
historically is limited to "front-office" operations such as
marketing, sales and service, the new feedback model requires a unified
view of the customer across the enterprise, including
"back-office" functions such as financial services,
manufacturing, supply chain management, enterprise resource management and
logistics.
How To Identify A Satisfied Customer: Low-Tech Solutions
Monitoring customer loyalty and retention is like assembling a jigsaw
puzzle: relevant information must be collected from across the
organization. To build a customer profile, think in terms of what data
exist where, and how best to organize and process these data.
What does a customer who is treating a company well look like? Ask
people in any department, they can tell you. The sales force will have no
trouble identifying satisfied customers. They refer new business.
Typically, the major accounts are prestige accounts, such as Fortune 500
companies, federal and state agencies and industry influencers. In
addition to their marquee value, these customers become strategic partners
and enter into multiyear, multiphase licensing and sales contracts. These
long-term relationships are built on collaboration and mutually beneficial
goals.
Ask marketing executives which customers treat them well and they will
use a different metric. Customer satisfaction is a willingness to "go
on record." Satisfied customers issue joint press announcements, are
the subjects of customer case studies and furnish product/service
endorsements (i.e., posted on the company Web site or used in marketing
and sales collateral material). As a further demonstration of loyalty,
these customers speak to the media on the company's behalf and appear at
its side at industry events and press conferences. Some may even agree to
appear in advertising as "a satisfied customer."
On the frontline (or firing line) of service and support issues,
customer support representatives have yet a different perspective.
Satisfied customers are those that rarely contact the support and service
teams. If they do, the caller's tone is friendly, and might be, "Hey,
we've encountered a glitch, I was hoping you could help us solve it,"
in contrast to, "Your - expletive deleted - product is
worthless!"
Even the finance department has a view into which customers are
satisfied. To them, it's the ones who pay their invoices on time.
Never overlook the personal touch. Strong working relationships, built
on good chemistry and trust, are another good predicator of customer
loyalty and retention.
As the above examples illustrate, companies actually know a great deal
about their customers. The question is how to analyze and use the
information to plan and forecast demand. The new paradigm shifts the
emphasis from what customers say (i.e., surveys, focus groups) to what
they do (i.e., repurchase products and pay on time).
The Economics Approach
Customer satisfaction surveys should be termed "lagging economic
indicators," as they measure what happened in the past. Notice how
many of the questions are phrased in the past tense: Did you receive the
information you needed? Was the product what you expected? In contrast,
"leading economic indicators" look to the future by tracking
customer loyalty and retention. Do you plan to repurchase this product or
service in the future? How can the offering be improved for future sales?
Customers vote with their wallets. Therefore, to benchmark their
satisfaction, study their purchasing behavior. Has the spending level
increased, decreased or stayed the same? Are new items appearing on
invoices? If so, are the ancillary products and services all related to
the original purchase, or are they branching into new company brands and
service areas? The latter is a surefire indication of customer loyalty and
retention.
How To Identify A Satisfied Customer: High-Tech Solutions
In many organizations, this mission-critical customer information is
fragmented across the enterprise. Each department has a customized IT
solution and maintains its own customer files. With data stored in
different silos, companies operate with huge information blind spots.
Moreover, it can take days, even weeks, to collect and analyze data from
multiple sources ' a competitive disadvantage in a 24/7 global market.
Some companies address this problem by hiring outside systems
integrators to build a data warehouse and consolidate customer data from
disparate systems. While a step in the right direction, this is far from
an ideal solution. Lacking a common structure, the merged data tries to
look and act the same, but incompatibility issues keep arising. Analytical
queries then can be inaccurate. For example, if the marketing department
uses a customer's middle initial and the service group omits it, the
system might not recognize "John J. Smith" and "John
Smith" as the same person. As a result, global synchronizations
cannot be performed reliably. Not only will duplicate files exist on Mr.
Smith, one may have his change of address while the other retains his
former location.
The optimal solution is to employ a single customer model across the
enterprise. E-business software solutions can leverage the Internet to
provide a platform to standardize, automate and streamline business
processes. With a central database, all parties can access, share and use
the same customer, supplier and partner information.
Today's collaborative CRM solutions can collect and synchronize data
from multiple knowledge sources: self-service, voice technologies (voice
over IP), Web sites, e-mail, video conferencing and face-to-face
interactions. Mirroring this change, traditional call centers have evolved
into multichannel customer interaction centers (CICs). The customer
service agent now has all the facts on screen: "Yes, I see that you
wrote a letter on May 12th disputing an item on your bill, and that you
followed up by phone on the 14th. Our finance department sent you a form
to fill out this week. If you'd like to speak to someone in that
department, I can transfer you now."
An integrated, single-data model also supports systemwide analytics.
With data mining, business intelligence and online analytical processing (OLAP)
built into the data architecture, companies can run any number and
combination of queries. The reports can be as simple as determining the
percentage of recipients who responded to an e-mail promotional offer, or
as complex as modeling a customer's lifetime value.
Using customer segmentation and profiling tools, service managers can
also create multiple levels of service. Not all customers are equal: some
accounts are highly profitable, others are money-losers. Therefore, when
measuring customer loyalty and retention, a company must factor in the
customer's relative value to the organization. Financial metrics should
not be the sole consideration. A single person account, such as an
industry guru or influential editor, can have a big impact on public
opinion and market reception.
A collaborative CRM system also improves customer service and support.
Let's look at how far-reaching the changes can be. With an automated
mobile service system, field visits can be intelligently scheduled based
on distances and real-time traffic conditions. As result, service people
show up on time. After the service call, the field agent can remotely
provide the office with real-time updates. The field report is accessible
instantly to CIC representatives, who may receive a call from the customer
in the wake of the visit. The data are entered automatically into the
sales and service contract management systems. Based on this report and
others like it, the product development team is alerted to the problem and
can take remedial action. With a more responsive, intelligent and
synchronized organization, customer satisfaction becomes a "team
effort."
How To Get Started
For companies interested in instituting the changes outlined above, we
recommend the following steps:
- Conduct a "customer information" audit. Map your entire
organization to determine which customer data reside where. Look at
what channels customers use to communicate. Understand how different
types of information are routed and answered. Understand the
distribution and frequency of all customer reports. How are they
analyzed and stored?
- Conduct a technical audit. In coordination with your IT group, look
at the deployment of customer databases. Discuss ways to centralize
and standardize customer information and how to integrate CRM with
front- and back-office functions. Find out if your IT vendors have
automated systems to help you mine your customer data.
- Create a customer-focused business model. Using the findings from
the dual audits, develop a customer-centric model that employs both
high-tech and low-tech strategies. Begin to measure customer value
more broadly, in terms of profitability, industry influence, public
relations support, technical feedback and future potential. Analyze
customer transactions and feedback to understand customer needs and
wants. Finally, shift the focus from customer satisfaction to the true
predicators of future growth and success: customer loyalty and
retention.
Beginning with these three steps, your company will benefit from the
paradigm shift in customer retention and increase profits as a result.
Instead of hoping to measure how you are treating your customers, you may
find improved insight into your business by understanding first how well
customers are treating you.
John Wookey is senior vice president, applications development, for
Oracle Corp.
1"The Loyalty Effect - The
Relationship Between Loyalty and Profits," Frederick F. Reichheld,
Robert G. Markey Jr. and Christopher Hopton, European Business Journal,
Autumn 2000 v12 i3, pp. 134.
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