CRM-The Technology

Technology is used to automate procedures, provide better information and to transform
entire business processes (Dedrick et al., 2003). These capabilities include not only
hardware and software, but also the technical and managerial expertise required to
provide reliable physical services and extensive electronic connectivity within and
outside a firm

Information on customers is critical to developing and maintaining customer
relationships. While small organizations with very few customers find it relatively easy to
collect and use relevant information in building customer relationships, larger
organizations find this practically impossible to do. Thus, information technology,
initially in the form of the database, was regarded as ‘an agent of surrogacy to be enlisted
to help marketers to re-create the operating styles of yesterday’s merchants’



CRM technology applications link front office (e.g. sales,marketing and customer service) and back office (e.g. finance, operations, logistics and
human resources) functions with the company’s customer “touch points” (Fickel, 1999).
A company’s touch points can include the Internet, e-mail, sales, direct mail,
telemarketing operations, call centres, advertising, fax, pagers, stores and kiosks. Often,
these touch points are controlled by separate information systems. CRM integrates touch
points around a common view of the customer (Eckerson and Watson, 2000).
CRM software and hardware applications drive three key processes:
(1) Automating business operations (sales automation, customer service, order
management etc.),

(2) Automating business performance processes ( data warehousing, data mining,
analytics etc.), and

(3) Automating communication and coordination processes (voice mail, e-mail, web
site etc.) (Crosby and Johnson 2001).

CRM is broadly implemented at two levels of an organization (Dyche, 2001), the
operational level and the strategic/analytical level. The operational level includes the
boundary spanning activities of the firm where direct customer contacts (touch points)
occur.
The other level of CRM implementation is called analytical CRM. Simply put, it involves
examining and comprehending customer interactions that occur at the touch points.
Analytical CRM entails the compilation of customer data into databases and its
subsequent analysis.

Creating, maintaining, and utilizing a data warehouse forms the coreof analytical CRM.
Data warehousing is the most important technology used in CRM. A
data warehouse can be defined as “a storage location for data that can support the
reporting and analytical needs of multiple departments across an organization. The data
may be time stamped to provide historical business information.” (patriot.net, nd)

Data warehousing technology makes CRM possible; data can be obtained and
manipulated easily. With this kind of technology analysing a customer’s data is easy. It is
possible to identify and report by product or service, geographic region, distribution
channel, customer group or individual customer (Story, 1998). An example of data
warehouse dimensions could be: customer, product, transaction, geography, time and
promotion.

Data mining is another important technology used in CRM systems and is defined
generally as “the process of analyzing data from different perspectives and summarizing
it into useful information - information that can be used to increase revenue, cut costs, or
both.” And it is defined technically as “the process of finding correlations or patterns
among dozens of fields in large relational databases” (Anderson, nd). Companies use data
mining to determine relationships between internal factors, such as price, and external
factors, such as competition.

Data mining makes it possible for companies to determine
the impact on customer satisfaction, sales and profit, which are essential to CRM.
Moreover, data mining is a way to drill down and view transactional data.
There are different types of patterns that can be found and analysed:
Classes: where you can locate data in predetermined groups. For example, a coffee shop
chain could mine customer purchase data to determine when they visit and what theybuy.

As a result, the coffee shop could have daily specials to increase the number of
customers on those certain days.

Clusters: where data items are grouped according to logical relationships or consumer
preferences.

Associations: where you can associate two or more data items. For example, when men
buy nappies they also buy beer. As a result, beers could be displayed near the nappies.
Sequential patterns: where you can determine a sequential pattern in purchasing two or
more items. For example, buying a camera and then buying a film every month
(anderson.ucla.edu, nd).

Data mining is used to predict the future of certain behaviour, and to identify the
existence of an item or an entry in the database. It is clear that data mining is essential to
CRM, since it is through analysing customer behaviour that an enterprise can determine
its marketing strategies, including advertising, design of catalogues and campaigns.
The essence of CRM is that a firm should integrate information with business action


Managerially it means that the data should be acted upon by managing
customer interactions at the touch points more effectively and efficiently.
Technologically, this calls for an integration of the “front end” and “back office”
systems. Some vendors like RightPoint, Manna and SAP provide the connection of the
front to the back end