Data Mining for Marketing Intelligence on the Internet

Maurice Mulvenna, AG Buchner, Marian Norwood

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper outlines the sources of data available in on-line retail sites, and explores how Internet marketing may be enhanced by using data mining techniques to discover behavioural and access patterns in the data sources. Data mining is the automated discovery of non-obvious, potentially useful and previously unknown information from large data sources. It use includes heuristic and artificial neural network techniques and induction algorithms to generate rules and associations that may be both useful and actionable. Within the context of relationship marketing data mining can provide knowledge about the unique characteristics of identified customer segments, so that business decisions may be made in relation to customer value and appropriate loyalty incentives can be developed. The potential of data mining is enormous, but its market application may be tempered by customers and consumer organisations who may react negatively to the collection and ‘mining’ of aggregated personal information.The implications are far reaching for Internet marketers, since data mining can improve their understanding of Internet consumer behaviour. It seems evident then, that Internet marketing activities will be characterised by sophisticated targeting of consumers. Ultimately, competitive advantage on the Internet may be determined by the ability of Internet marketers to collect and manage customer databases. The paper concludes by describing the research objectives of MIMIC, a new ESPRIT research project funded under the Electronic Commerce thematic call. The MIMIC (Mining the Internet for Marketing IntelligenCe) project applies data mining techniques to Internet data.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages12
Publication statusAccepted/In press - 24 Jun 1998
EventCompeting in Information Society Conference 1998 (CIS-98) (ESPRIT Conference) - Genoa
Duration: 24 Jun 1998 → …

Conference

ConferenceCompeting in Information Society Conference 1998 (CIS-98) (ESPRIT Conference)
Period24/06/98 → …

Fingerprint

Data mining
Marketing intelligence
World Wide Web
Internet marketing
Marketers
Data sources
Heuristics
Data base
Electronic commerce
Induction
Consumer behaviour
Personal information
Competitive advantage
Targeting
Marketing activities
Incentives
Retail
Artificial neural network
Customer value
Loyalty

Keywords

  • Data Mining
  • Electronic Commerce
  • Marketing Intelligence

Cite this

Mulvenna, M., Buchner, AG., & Norwood, M. (Accepted/In press). Data Mining for Marketing Intelligence on the Internet. In Unknown Host Publication
Mulvenna, Maurice ; Buchner, AG ; Norwood, Marian. / Data Mining for Marketing Intelligence on the Internet. Unknown Host Publication. 1998.
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title = "Data Mining for Marketing Intelligence on the Internet",
abstract = "This paper outlines the sources of data available in on-line retail sites, and explores how Internet marketing may be enhanced by using data mining techniques to discover behavioural and access patterns in the data sources. Data mining is the automated discovery of non-obvious, potentially useful and previously unknown information from large data sources. It use includes heuristic and artificial neural network techniques and induction algorithms to generate rules and associations that may be both useful and actionable. Within the context of relationship marketing data mining can provide knowledge about the unique characteristics of identified customer segments, so that business decisions may be made in relation to customer value and appropriate loyalty incentives can be developed. The potential of data mining is enormous, but its market application may be tempered by customers and consumer organisations who may react negatively to the collection and ‘mining’ of aggregated personal information.The implications are far reaching for Internet marketers, since data mining can improve their understanding of Internet consumer behaviour. It seems evident then, that Internet marketing activities will be characterised by sophisticated targeting of consumers. Ultimately, competitive advantage on the Internet may be determined by the ability of Internet marketers to collect and manage customer databases. The paper concludes by describing the research objectives of MIMIC, a new ESPRIT research project funded under the Electronic Commerce thematic call. The MIMIC (Mining the Internet for Marketing IntelligenCe) project applies data mining techniques to Internet data.",
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Mulvenna, M, Buchner, AG & Norwood, M 1998, Data Mining for Marketing Intelligence on the Internet. in Unknown Host Publication. Competing in Information Society Conference 1998 (CIS-98) (ESPRIT Conference), 24/06/98.

Data Mining for Marketing Intelligence on the Internet. / Mulvenna, Maurice; Buchner, AG; Norwood, Marian.

Unknown Host Publication. 1998.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - This paper outlines the sources of data available in on-line retail sites, and explores how Internet marketing may be enhanced by using data mining techniques to discover behavioural and access patterns in the data sources. Data mining is the automated discovery of non-obvious, potentially useful and previously unknown information from large data sources. It use includes heuristic and artificial neural network techniques and induction algorithms to generate rules and associations that may be both useful and actionable. Within the context of relationship marketing data mining can provide knowledge about the unique characteristics of identified customer segments, so that business decisions may be made in relation to customer value and appropriate loyalty incentives can be developed. The potential of data mining is enormous, but its market application may be tempered by customers and consumer organisations who may react negatively to the collection and ‘mining’ of aggregated personal information.The implications are far reaching for Internet marketers, since data mining can improve their understanding of Internet consumer behaviour. It seems evident then, that Internet marketing activities will be characterised by sophisticated targeting of consumers. Ultimately, competitive advantage on the Internet may be determined by the ability of Internet marketers to collect and manage customer databases. The paper concludes by describing the research objectives of MIMIC, a new ESPRIT research project funded under the Electronic Commerce thematic call. The MIMIC (Mining the Internet for Marketing IntelligenCe) project applies data mining techniques to Internet data.

AB - This paper outlines the sources of data available in on-line retail sites, and explores how Internet marketing may be enhanced by using data mining techniques to discover behavioural and access patterns in the data sources. Data mining is the automated discovery of non-obvious, potentially useful and previously unknown information from large data sources. It use includes heuristic and artificial neural network techniques and induction algorithms to generate rules and associations that may be both useful and actionable. Within the context of relationship marketing data mining can provide knowledge about the unique characteristics of identified customer segments, so that business decisions may be made in relation to customer value and appropriate loyalty incentives can be developed. The potential of data mining is enormous, but its market application may be tempered by customers and consumer organisations who may react negatively to the collection and ‘mining’ of aggregated personal information.The implications are far reaching for Internet marketers, since data mining can improve their understanding of Internet consumer behaviour. It seems evident then, that Internet marketing activities will be characterised by sophisticated targeting of consumers. Ultimately, competitive advantage on the Internet may be determined by the ability of Internet marketers to collect and manage customer databases. The paper concludes by describing the research objectives of MIMIC, a new ESPRIT research project funded under the Electronic Commerce thematic call. The MIMIC (Mining the Internet for Marketing IntelligenCe) project applies data mining techniques to Internet data.

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Mulvenna M, Buchner AG, Norwood M. Data Mining for Marketing Intelligence on the Internet. In Unknown Host Publication. 1998