Decision Support Systems thirty-one Ž2001. 127–137 www.elsevier.comrlocaterdsw
Understanding management and data exploration for advertising
Michael T. Shaw a, b, c, ), Chandrasekar Subramaniam a, Gek Woo Tan a, Michael Electronic. Welge m c
Department of Organization Administration, UniÕersity of The state of illinois at Urbana-Champaign, Urbana, IL, USA Countrywide Center intended for Supercomputing Applications (NCSA), UniÕersity of Illinois at Urbana-Champaign, Urbana, ELLE, USA Beckman Institute, UniÕersity of The state of illinois at Urbana-Champaign, Room 2051, 405 D. Mathews AÕenue, Urbana, IL 61801, UNITED STATES b
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. Nevertheless , much of the useful marketing observations into client characteristics and their purchase habits are mainly hidden and untapped. Current emphasis on client relationship supervision makes the promoting function an excellent application region to tremendously benefit from the make use of data mining tools intended for decision support. A systematic strategy that uses data exploration and know-how management methods is proposed to manage the marketing know-how and support marketing decisions. This methodology can be the basis for enhancing customer romantic relationship management. queen 2001 Elsevier Science N. V. Most rights reserved. Keywords: Info mining; Understanding management; Marketing decision support; Customer romance management
1 . Introduction In recent times, the creation of information technology provides transformed the way in which marketing is done and how businesses manage information regarding their customers. The availability of large amount of data upon customers, made possible by fresh information technology tools, has created chances as well as challenges for businesses to leverage your data and gain competitive benefits. Wal-Mart, the largest retailer in the U. T., for example , provides a customer repository that contains about 43 tera-bytes of data, ) Corresponding creator. Beckman Institute, University of Illinois by Urbana-Champaign, Room 2051, 405 N. Mathews Avenue, Urbana, IL 61801, USA. Tel.: q 1-217-244-1266; fax: queen 1-217244-8371. Email-based address: [email protected] edu ŽM. J. Shaw..
which is larger than the database used by the interior Revenue Companies for collecting income taxes w10x. The Internet and the World Wide Web make the process of collecting data easier, adding to the volume of data available to businesses. On the other hand, many agencies have realized the knowledge in these huge directories are key to supporting the various organizational decisions. Particularly, the ability about clients from these types of databases is critical for the marketing function. But , a lot of this valuable knowledge is usually hidden and untapped. However, the intense competition and elevated choices readily available for customers have created new pressures on promoting decision-makers and there has appeared a need to control customers in a long-term romance. This new trend, called customer relationship management, requires which the organizations customize their products and ser-
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Meters. J. Shaw et al. r Decision Support Systems 31 (2001) 127–137
vices and connect to their customers based upon actual buyer preferences, instead of some thought general attributes w21, 22x. As companies move towards customer relationship management, the marketing function, as the front-line to interact with customers, is the most impacted due to these types of changes. There exists an increasing recognition that powerful customer romance management is possible only based on a true knowledge of the needs and tastes of the buyers. Under these conditions, info mining equipment can help find out the hidden knowledge and understand client better, although a systematic know-how management work...