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The ‘Soft-Push’: Mining Internet Data for Marketing Intelligence

Mulvenna, Maurice, Buchner, AG, Norwood, Marian and Grant, C (1997) The ‘Soft-Push’: Mining Internet Data for Marketing Intelligence. In: Working Conference Electronic Commerce in the Framework of Mediterranean Countries Development (EUROMED). EUROMED. 12 pp. [Conference contribution]

[img] Text - Accepted Version


This paper examines the challenges that on-line shopping and other commercial transactions on the Internet pose for marketers in the retail industry. The Internet constitutes a whole new marketplace in its own right, and evidence exists that the traditional manipulation of the marketing mix has to be modified for this new environment. To place this paper in context, the authors describe the potential growth of electronic commerce on the Internet, how traditional marketing strategies can be adapted for the Internet and current Internet marketing techniques. This paper highlights how marketing professionals and retailers can exploit the tools of the Internet to move closer to their customers and add value to their products. It outlines the potential for applying data mining technology to the data that is collected as consumers browse and purchase goods and services in on-line shopping malls. The authors introduce a variation of the push promotional strategy - ‘the soft-push’ - a sales promotion strategy based on the navigational and purchasing behaviour of on-line shoppers. Data mining allows marketers to reveal customer profiles, helping to identify appropriate market segments. Different data algorithms are described and the data mining process is explained. A comparison is made between the ‘soft-push’ approach and other web mining approaches. In conclusion, key ethical questions are posed and the implications of data mining for marketers are summarised.

Item Type:Conference contribution (Paper)
Keywords:Electronic Commerce, Personalisation, Marketing Intelligence, Data Mining
Faculties and Schools:Faculty of Computing & Engineering
Ulster Business School > Department of International Business
Faculty of Computing & Engineering > School of Computing and Mathematics
Ulster Business School
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:36510
Deposited By: Professor Maurice Mulvenna
Deposited On:13 Jan 2017 09:41
Last Modified:17 Oct 2017 16:26

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