More than Data Warehouse- An insight to Customer Information Ritu Aggrawal – firstname.lastname@example.org
Deepshikha Kalra -email@example.com
working with MERI affiliated to GGSIPU, Delhi
The business requirements of an enterprise are constantly changing and the changes are coming at an exponential rate. Like advances in Information Technology have helped companies to quickly match competition. As a result, product quality and cost are no longer significant competitive advantages. Therefore today , firms are adopting a more customer centric approach to leverage on their real competitive advantages i.e. their customers. The punch line for today is “know your customer” but the irony is that companies have lot of data but its difficult to extract information from it. Or in other words one can say data, data everywhere, but never the time to think. Advances in data storage and processing technologies have made it possible today to store very large amount of data in what are called Data Warehouse and then uses Data Mining tools to extract relevant information , which will help us in knowing how the customer will behave in order to facilitate strategic decision making.
This paper is divided in various sections. The first section throws the light on customer, data , information and correlation among the three entities. Further the need of data for better implementation of Customer Relationship Management following with the introduction of the Data Warehouse. The next section discusses the architecture of Data Warehouse giving way to analytical processing . In this paper , we wish to bring out the importance of Data Mining in the process of CRM. The last section discusses CRM, the main ideas behind it and how Data Mining fits in the process of CRM. Subsequently with the various Data Mining tools like Market Basket Analysis (MBA) and cluster Analysis etc .relevant to CRM and various live cases of different firms related to effective CRM implementation using Data Mining tools to support our research and finally paper is concluded in the last section.
Data warehouse (DW), Data mining, Market Basket Analysis(MBA), Cluster Analysis, Business Intelligence(BI), On Line Analytical Processing (OLAP) , Extract, Transform and Load (ETL), Customer Relationship Management (CRM).
Today’s marketplace isn’t the same as the one we’re used to even though many of the basic principles haven’t changed. Events in the external market place are forcing us to rethink what we have to do internally in order to remain successful. Till recently, marketing has been understood as an advancement of sales that could add a little of marketing research, advertising and after sales service. Liberalization in the Indian industries in general and service sector in particular has created options in front of customers. As a result “Customer loyalty” has become the buzzword in today’s scenario. The shift in the psychology of customers forced policy makers of companies to assign due importance to marketing decision and realize about the importance of customer retention leading way to customer relationship management Customer relationship management is the automation of horizontally integrated business processes involving “front office” customer touch points – sales (contact management, product configuration) marketing (campaign management, marketing), & customer service (called data centre, field service) via multiple, interconnected delivery channels. (telephone, e-mails, web, direct interaction), The CRM application architecture must combine both operational (transaction – oriented business process management) technologies. In short CRM is a technology initiative that aims to strengthen the front-end operations and build a mutually valuable long-term relationship with the customers.
CUSTOMER and DATA
Today advances in information technology, networking & manufacturing technologies have helped...
References:  Michael J A Berry , Gordon S Linoff – Mastering Data Mining – The Art and Science of customer relationship management , Wiley , 2001
 Paul Greenberg – CRM – At the speed of light; ThirdEdition; Tata McGrawHill, _2004
 Paulraj Ponniah, Data Warehousing Fundamentals, A Comprehensive Guide For IT Professionals, Wiley Publications, 2005
. Punj, Girish and David w
 Roger J. Baran, Robert J.Galka & Daniel P. Strunk, Customer Relationship Management, Cengage Learning, 2007.
 S. Nagabhushana – Data Warehousing (OLAP & Data Mining); First Edition; New Age Publicationl, 2006
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