Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Explorative multi-objective optimization of marketing campaigns for the fashion retail industry
Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). Univ Boras, Dept Informat Technol, Boras, Sweden.
Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). Univ Boras, Dept Informat Technol, Boras, Sweden.ORCID iD: 0000-0003-0274-9026
Jönköping University, School of Engineering, JTH, Computer Science and Informatics, JTH, Jönköping AI Lab (JAIL). Univ Boras, Dept Informat Technol, Boras, Sweden.ORCID iD: 0000-0003-0412-6199
2018 (English)In: Data Science And Knowledge Engineering For Sensing Decision Support / [ed] Liu, J, Lu, J, Xu, Y, Martinez, L & Kerre, EE, World Scientific, 2018, Vol. 11, 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 pro fit. 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
World Scientific, 2018. Vol. 11, p. 1551-1558
Series
World Scientific Proceedings Series on Computer Engineering and Information Science ; 11
Keywords [en]
Association rules; marketing; visualization; Pareto front
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-44349DOI: 10.1142/9789813273238_0193ISI: 000468160600193ISBN: 978-981-3273-24-5 (electronic)ISBN: 978-981-3273-22-1 (print)OAI: oai:DiVA.org:hj-44349DiVA, id: diva2:1322784
Conference
13th International Conference on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS), Belfast, Ireland, 21-24 August, 2018
Available from: 2019-06-11 Created: 2019-06-11 Last updated: 2019-08-22Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Sundell, HåkanLöfström, TuweJohansson, Ulf

Search in DiVA

By author/editor
Sundell, HåkanLöfström, TuweJohansson, Ulf
By organisation
JTH, Jönköping AI Lab (JAIL)
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 42 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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