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Personalized Product Recommendations: Evidence from the Field

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dc.contributor.author Pöyry, Essi
dc.contributor.author Hietaniemi, Ninni
dc.contributor.author Parvinen, Petri
dc.contributor.author Hamari, Juho
dc.contributor.author Kaptein, Maurits
dc.date.accessioned 2016-12-29T01:28:19Z
dc.date.available 2016-12-29T01:28:19Z
dc.date.issued 2017-01-04
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41626
dc.description.abstract Targeting personalized product recommendations to individual customers has become a mainstream activity in online stores as it has been shown to increase click-through rate and sales. However, as personalization becomes increasingly commonplace, customers may feel personalized content intrusive and therefore not responding or even avoiding them. Many studies have investigated advertising intrusiveness and avoidance but a research gap on the effect of degree of personalization on customer responses based on field evidence exists. In this paper, 27,175 recommendation displays from five different online stores are analyzed. The results show that the further the customer is in the purchasing process, the more effective personalization is if it is based on information about the present rather than past browsing session. Moreover, recommendations in passive form are more effective than recommendations in active form suggesting the need to dispel the perception of intrusiveness.
dc.format.extent 9 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject personalized product recommendations
dc.subject click-through rate
dc.subject advertising intrusiveness
dc.subject e-commerce
dc.title Personalized Product Recommendations: Evidence from the Field
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2017.467
Appears in Collections: Customer Analytics and Data-Led Omnichannel Commerce Minitrack


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