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Explorative multi-objective optimization of marketing campaigns for the fashion retail industry
Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT. (CSL@BS)
Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT. (CSL@BS)ORCID-id: 0000-0003-0274-9026
Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT. (CSL@BS)
2018 (engelsk)Inngår i: Data Science and Knowledge Engineering for Sensing Decision Support / [ed] Jun Liu, Jie Lu, Yang Xu, Luis Martinez and Etienne E Kerre, 2018, s. 1551-1558Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
2018. s. 1551-1558
Emneord [en]
Association rules, marketing, visualization, Pareto front
HSV kategori
Forskningsprogram
Handel och IT
Identifikatorer
URN: urn:nbn:se:hb:diva-15138OAI: oai:DiVA.org:hb-15138DiVA, id: diva2:1252471
Konferanse
FLINS 2018, Belfast, August 21-24, 2018.
Forskningsfinansiär
Knowledge Foundation, 20160035Tilgjengelig fra: 2018-10-01 Laget: 2018-10-01 Sist oppdatert: 2020-01-29bibliografisk kontrollert

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