متن انگلیسی مقاله ارانه شده امتحان استراتژی

Abstract

Due to the proliferation of information systems and technology, businesses increasingly have the capability to accumulate huge amounts of customer data in large databases.

 However, much of the useful marketing insights into customer

characteristics and their purchase patterns are largely hidden and untapped.

Current emphasis on customer relationship management makes the marketing function an ideal application area to greatly benefit from the use of data mining tools for

decision support.

A systematic methodology that uses data mining and knowledge management techniques is proposed to manage the marketing knowledge and support marketing decisions. This methodology can be the basis for enhancing customer relationship management.

  Introduction

In recent years, the advent of information technology

has transformed the way marketing is done and

how companies manage information about their customers.

The availability of large volume of data on

customers, made possible by new information technology

tools, has created opportunities as well as

challenges for businesses to leverage the data and

gain competitive advantage.

Wal-Mart, the largest retailer in the U.S.,

for example, has a customer database that

contains around 43 tera-bytes of data,

which is larger than the database used by the Internal

Revenue Services for collecting income taxes.

The Internet and the World Wide Web have made

the process of collecting data easier, adding to the

volume of data available to businesses. On the one

hand, many organizations have realized that the

knowledge in these huge databases are key to supporting

the various organizational decisions.

Particularly,the knowledge about customers from

These databases is critical for the marketing function.

But,much of this useful knowledge is hidden and untapped.

On the other hand, the intense competition and

increased choices available for customers have

created new pressures on marketing decision-makers

and there has emerged a need to manage customers

in a long-term relationship.

This new phenomenon, called customer relationship management,

requires that the organizations tailor their products and services

and interact with their customers based on

actual customer preferences, rather than some assumed

general characteristics.

As organizations move towards customer relationship management,

the marketing function, as the front-line to interact with customers,

is the most impacted due to these changes.

There is an increasing realization that

effective customer relationship management can be

done only based on a true understanding of the needs

and preferences of the customers. Under these conditions,

data mining tools can help uncover the hidden

knowledge and understand customer better, while a

systematic knowledge management effort can channel

the knowledge into effective marketing strategies.

This makes the study of the knowledge extraction

and management particularly valuable for marketing.

Developments in database processing,

data warehousing, machine learning

and knowledge management have contributed

greatly to our understanding of the data mining process.

More recent research on data mining

and knowledge discovery  has further enhanced

our understanding of the application of data

mining and the knowledge discovery process. But,

most research has focused on the theoretical and

computational process of pattern discovery and a

narrow set of applications such as fraud detection or

risk prediction. Given the important role played by

marketing decisions in the current customer-centric

environment, there is a need for a simple and integrated

framework for a systematic management of

customer knowledge. But, there is a surprising lack

of a simple and overall framework to link the extraction

of customer knowledge with the management

and application of the knowledge, particularly in the

context of marketing decisions. While data mining

studies have focused on the techniques, customer

relationship studies have focused on the interface to

the customer and the strategies to manage customer

interactions. True customer relationship management

is possible only by integrating the knowledge discovery

process with the management and use of the

knowledge for marketing strategies. This will help

marketers address customer needs based on what the

marketers know about their customers, rather than a

mass generalization of the characteristics of customers

We address this issue in this paper by presenting

an integrated framework for knowledge discovery

and management, in the context of marketing decisions.

Marketing decisions based on discovered

customer knowledge leads to knowledge-based Marketing.