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dc.contributor.authorMogaji, Emmanuel
dc.contributor.authorOlaleye, Sunday
dc.contributor.authorUkpabi, Dandison
dc.contributor.editorRana, Nripendra P.
dc.contributor.editorSlade, Emma L.
dc.contributor.editorSahu, Ganesh P.
dc.contributor.editorKizgin, Hatice
dc.contributor.editorSingh, Nitish
dc.contributor.editorDey, Bidit
dc.contributor.editorGutierrez, Anabel
dc.contributor.editorDwivedi, Yogesh K.
dc.date.accessioned2019-12-27T08:29:46Z
dc.date.available2019-12-27T08:29:46Z
dc.date.issued2020
dc.identifier.citationMogaji, E., Olaleye, S., & Ukpabi, D. (2020). Using AI to Personalise Emotionally Appealing Advertisement. In N. P. Rana, E. L. Slade, G. P. Sahu, H. Kizgin, N. Singh, B. Dey, A. Gutierrez, & Y. K. Dwivedi (Eds.), <i>Digital and Social Media Marketing : Emerging Applications and Theoretical Development</i> (pp. 137-150). Springer. Advances in Theory and Practice of Emerging Markets. <a href="https://doi.org/10.1007/978-3-030-24374-6_10" target="_blank">https://doi.org/10.1007/978-3-030-24374-6_10</a>
dc.identifier.otherCONVID_33889705
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/67008
dc.description.abstractPersonal data and information collected online by companies can be used to design and personalise advisements. This chapter extends existing research into the online behavioural advertising by proposing a model that incorporates artificial intelligence and machine learning into developing emotionally appealing advertisements. It is proposed that big data and consumer analytics collected through AI from different sources will be aggregated to have a better understanding of consumers as individuals. Personalised emotionally appealing advertisements will be created with this information and shared digitally using pragmatic advertising strategies. Theoretically, this chapter contributes towards the use of emerging technologies such as AI and Machine Learning for Digital Marketing, big data acquisition, management and analytics and its impact on advertising effectiveness. With customer analytics making up a more significant part of big data use in sales and marketing and GDPR ensures data are legitimately collected and processed, there are practical implications for Managers as well. Acknowledging that this is a conceptual model, the critical challenges are presented. This is open for future research and development both from academic, digital marketing practitioners and computer scientists.en
dc.format.extent339
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofDigital and Social Media Marketing : Emerging Applications and Theoretical Development
dc.relation.ispartofseriesAdvances in Theory and Practice of Emerging Markets
dc.rightsIn Copyright
dc.subject.otherartificial intelligence
dc.subject.otheronline behavioural advertising
dc.subject.otherpersonalised ad
dc.subject.otheremotional appeal
dc.subject.othersocial media
dc.titleUsing AI to Personalise Emotionally Appealing Advertisement
dc.typebookPart
dc.identifier.urnURN:NBN:fi:jyu-201912275482
dc.contributor.laitosKauppakorkeakoulufi
dc.contributor.laitosSchool of Business and Economicsen
dc.type.urihttp://purl.org/eprint/type/BookItem
dc.relation.isbn978-3-030-24373-9
dc.description.reviewstatuspeerReviewed
dc.format.pagerange137-150
dc.relation.issn2522-5006
dc.type.versionacceptedVersion
dc.rights.copyright© Springer Nature Switzerland AG, 2020
dc.rights.accesslevelopenAccessfi
dc.subject.ysotekoäly
dc.subject.ysososiaalinen media
dc.subject.ysotäsmämarkkinointi
dc.subject.ysoverkkomainonta
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p2616
jyx.subject.urihttp://www.yso.fi/onto/yso/p20774
jyx.subject.urihttp://www.yso.fi/onto/yso/p5877
jyx.subject.urihttp://www.yso.fi/onto/yso/p15152
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1007/978-3-030-24374-6_10


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