Customer relationship management is a combination of several
components. Before the process can begin, the firm must first possess customer
information. Companies can learn about their customers through internal
customer data or they can purchase data from outside sources. There are several
sources of internal data:
_ summary tables
that describe customers (e.g., billing records)
_ customer surveys
of a subset of customers who answer detailed questions
_ behavioral data
contained in transactions systems (web logs, credit card records,
etc).
An enterprise data warehouse is a critical component of a
successful CRM strategy. Most firms have massive databases that contain
marketing, HR, and financial information. However, the data required for CRM
can be limited to a marketing data mart with limited feeds from other corporate
systems.
CRM system must analyze the data using statistical tools,
OLAP, and data mining. Whether the firm uses traditional statistical techniques
or one of the data mining software tools, marketing professionals need to
understand the customer data and business imperatives.
The term “customer
lifecycle” refers to the stages in the relationship between a customer and a
business. It is important to understand customer lifecycle because it relates
directly to customer revenue and customer profitability. Marketers say there are
three ways to increase a customer’s value: (1) increase their use (or
purchases) of products they already have; (2) sell them more or higher-margin
products; and (3) keep the customers for a longer period of time.
The customer lifecycle provides a good framework for applying
data mining to CRM. On the “input” side of data mining, the customer lifecycle
tells what information is available. On the “output” side, the customer
lifecycle tells what is likely to be interesting