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Customer Relationship Management (CRM)

History and theory: customer relationship management

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Field concerns and data collection: customer data integration

Customer Relationship Management (CRM) is growing in importance due to the challenging business
environment faced by organizations throughout the world today. It is particularly critical in industries
undergoing changes in traditional channel configuration. CRM is a means of addressing increasing
competition, changing economic conditions and promotional dependence through the use of intimate
customer knowledge; knowledge gained through relationship development and past marketing programs.
CRM is increasing in prominence because it focuses on current users who are the source of the
majority of business revenue and the best option for improving business in uncertain times.

There are a number of working definitions for CRM. In fact the letters CRM have been used to identify
Continuous Relationship Marketing, Customer Relationship Marketing and Customer Relationship
Management. Each term represents the same process. CRM can be defined as a process that maximizes
customer value through on-going marketing activity founded on intimate customer knowledge
established through collection, management and leverage of customer information and contact history.
CRM is about perfecting relationships to maximize a customer's value over time.

CRM is part of an evolution in corporate thinking that began with the Enterprise Resource Planning
(ERP) initiative of the 1990's. ERP forces all resources within a corporation to work within one business
system. In the 1990's, over $300 billion was spent on centralizing, standardizing and organizing
information and resources throughout U.S. corporations. The results, however, have been mixed in
terms of payout. What is indisputable is that the information system processing skills acquired in implementing
ERP programs enabled many organizations to support CRM and E-commerce programming;
initiatives not in existence when ERP began. CRM was developed, in large part, as a result of
data mining, or segmentation and targeting research, made possible from the centralization of customer
records. Organizations began to realize that they could better serve customers since they better
understood customers.

CRM has benefited from advances in data management and middleware new software that allows
disparate data resources to work as a single integrated database. CRM has also been supported by a
new generation of promotional tools; for example, selective binding, variable valuation and new probabilistic
targeting tools such as Spectra. In the U.S., CRM is now practiced by approximately 45% of
the companies in retailing, aircraft and utilities; 50-55% of the companies in financial services, pharmaceuticals
and transportation; and 70% of the companies in telecommunications and credit.

The development and popularity of electronic marketing as a tool has produced a rich source of consumer
data for access by organizations in many industries. Focusing on the retail grocery industry in
the U.S., Frequent Shopper Programs (FSP's), are used by grocery retailers who comprise over 60% of
the All Commodity Volume. They have produced consumer files that will be the key to more profitable
grocery promotion for them in the future. Companies like Safeway, Kroger and American stores
are heavily invested in these programs. Frequent shopper programs in the grocery industry developed
as loyalty program extensions. These programs are consumer card-based programs that track purchases
based on the use of scanners and reward customers with discounts based on brands purchased.

These programs were developed to provide customers with an additional reason to increase their share
of purchase in a particular chain of stores.

The concept of customer lifetime value, the money value of a customer relationship over time, has
evolved to enable savvy direct marketers the opportunity to differentiate the profit potential for each of
the various market segments that they serve. Loyalty marketing has always focused on the fact that
retaining and improving business with current consumers costs less than acquiring new customers.
Customer retention, as a strategy, is founded on the ability to segment and differentially target current
users to improve the value of the relationship for both seller and buyer.

Lifetime value is calculated by identifying the revenue stream over a period in time, applying a retention
rate for each year, subtracting total cost and then applying a discount rate to gross profit in order
to determine the net present value of a customer. The calculation is completed for a number of years
using different retention rates. Midas Mufflers uses customer lifetime value as the backbone for their
direct marketing efforts. Midas tracks cars based on vehicle mileage and contacts customers to remind
them of service and brake opportunities over the life of their vehicle.

There is a difference between Frequent Shopper Programs and Loyalty Focused Programs. For example,
in the U.S. grocery industry today, the focus for supermarkets is on promotion rather than on the
development of comprehensive loyalty programs.

Customers participate in these programs in large part to ensure they earn the lowest possible discount,
not because of any loyalty to a retailer.

Less than half of all managers believe that their CRM programs are attaining corporate objectives despite
the advances made in data technology, ERP, new software linking databases, e-commerce and
customer loyalty programming. The problems with CRM to date have been the following: lack of
overall project responsibility, poorly written objectives, and inferior technical performance. Many feel
that the results for CRM to-date have been disappointing. However, we are early in the effort. Required
for improvement are the establishment of clearly stated objectives, the establishment of organizational
authority and improvements in the use of information technology. These will be discussed in
following sections.

Segmentation is the process of placing individuals or organizations who have similar needs into
groups. Target segments are selected based on an organization's ability to satisfy respective segments'
needs. Organizations match benefits with the respective needs of sub-segments by developing positioning
strategies for each sub segment. CRM professes that markets are "segments-of-one". However,
it is not feasible to create a specific segmentation and subsequent positioning strategy for each
individual. So, the question arises as to how one can successfully manage "segments-of-one"? The
following is an example of how traditional segmentation and the techniques required for "segmentsof-
one" can be integrated in a CRM effort.

A major Gaming Corporation began implementing a CRM strategy across four of their hotel and casino
properties. Traditional segmentation techniques were initially used to define their customer and
prospect market. The most promising segment was based on a psychographic variable "risk". This
segment consisted of small business owners. Other segments were based upon geographic location (instate
versus out-of-state), frequency of visits and length of visits. Sub-segments consisted of those
individuals who gambled at the slot machines and those who gambled at tables. While a person could
play both slots and tables, there was a propensity for one or the other. Within these segments a person
could either gamble at the casino and stay in that casino's hotel, gamble at the casino and stay at another
hotel or stay at the hotel but gamble at another casino. There was also the segment of potential
gamblers who stayed at the hotel but were not gambling.

The next step for the Gaming Corporation was to focus on each individual. Over 100 demographic,
psychographics, lifestyle and behavioral variables were captured and maintained on each individual.
These variables served as CRM enablers. An individual's Lifetime Value (LTV) was calculated.
LTV was combined with an individual's theoretical wins and losses in a real time environment (as the
person was gambling) to determine an appropriate CRM strategy.

Data on an individual's gambling was captured from slot machines via a card the customer swiped
through the machine. Casino personnel captured table play activity. The key was that they knew the
individual and could monitor that person's theoretical wins and losses. They were trained to monitor
ten individuals concurrently and enter that information into a networked computer every hour. If a
person was losing a considerable amount in a session, the CRM system would recommend a monetary
value for a specific CRM initiative. The respective variables would be used in support of compensation
to the individual.

For example, if a person is staying at the property and preferred a certain restaurant or type of entertainment,
reservations could be made for dining and a show--with the house paying the tab. CRM efforts
are also possible even if an individual is staying with another hotel--perhaps a gift of one's favorite
perfume fragrance or a new dress--clothing size having been captured through the CRM effort. Or
for gamblers identified as golf enthusiasts and slot players, a solicitation could be sent asking the individual
to attend a combination golf and slot tournament for a three-day stay.

  1. History and theory: customer relationship management
  2. Field concerns and data collection: customer data integration
  3. Issues regarding communication and CRM: social issue, consumer privacy
  4. Future of CRM: future, customer relationship marketing, McKinsey study