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Explorative multi-objective optimization of marketing campaigns for the fashion retail industry
University of Borås, Faculty of Librarianship, Information, Education and IT. (CSL@BS)
University of Borås, Faculty of Librarianship, Information, Education and IT. (CSL@BS)ORCID iD: 0000-0003-0274-9026
University of Borås, Faculty of Librarianship, Information, Education and IT. (CSL@BS)
2018 (English)In: Data Science and Knowledge Engineering for Sensing Decision Support / [ed] Jun Liu, Jie Lu, Yang Xu, Luis Martinez and Etienne E Kerre, 2018, p. 1551-1558Conference paper, Published paper (Refereed)
Abstract [en]

We show how an exploratory tool for association rule mining can be used for efficient multi-objective optimization of marketing campaigns for companies within the fashion retail industry. We have earlier designed and implemented a novel digital tool for mining of association rules from given basket data. The tool supports efficient finding of frequent itemsets over multiple hierarchies and interactive visualization of corresponding association rules together with numerical attributes. Normally when optimizing a marketing campaign, factors that cause an increased level of activation among the recipients could in fact reduce the profit, i.e., these factors need to be balanced, rather than optimized individually. Using the tool we can identify important factors that influence the search for an optimal campaign in respect to both activation and profit. We show empirical results from a real-world case-study using campaign data from a well-established company within the fashion retail industry, demonstrating how activation and profit can be simultaneously targeted, using computer-generated algorithms as well as human-controlled visualization.

Place, publisher, year, edition, pages
2018. p. 1551-1558
Keywords [en]
Association rules, marketing, visualization, Pareto front
National Category
Computer Sciences
Research subject
Business and IT
Identifiers
URN: urn:nbn:se:hb:diva-15138OAI: oai:DiVA.org:hb-15138DiVA, id: diva2:1252471
Conference
FLINS 2018, Belfast, August 21-24, 2018.
Funder
Knowledge Foundation, 20160035Available from: 2018-10-01 Created: 2018-10-01 Last updated: 2020-01-29Bibliographically approved

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Sundell, HåkanLöfström, TuveJohansson, Ulf

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • harvard-cite-them-right
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf