University of Oulu

Mogaji E., Olaleye S., Ukpabi D. (2020) Using AI to Personalise Emotionally Appealing Advertisement. In: Rana N. et al. (eds) Digital and Social Media Marketing. Advances in Theory and Practice of Emerging Markets. Springer, Cham. https://doi.org/10.1007/978-3-030-24374-6_10

Using AI to personalise emotionally appealing advertisement

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Author: Mogaji, Emmanuel1; Olaleye, Sunday2; Ukpabi, Dandison3
Organizations: 1University of Greenwich, London, UK
2University of Oulu, Oulu, Finland
3University of Jyväskylä, Jyväskylä, Finland
Format: article
Version: accepted version
Access: embargoed
Persistent link: http://urn.fi/urn:nbn:fi-fe2019111943217
Language: English
Published: Springer Nature, 2020
Publish Date: 2021-11-12
Description:

Abstract

Personal 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.

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Series: Advances in theory and practice of emerging markets
ISSN: 2522-5006
ISSN-L: 2522-5006
ISBN: 978-3-030-24374-6
ISBN Print: 978-3-030-24373-9
Pages: 137 - 150
DOI: 10.1007/978-3-030-24374-6_10
OADOI: https://oadoi.org/10.1007/978-3-030-24374-6_10
Host publication: Digital and Social Media Marketing
Host publication editor: Rana, Nripendra P.
Slade, Emma L.
Sahu, Ganesh P.
Kizgin, Hatice
Singh, Nitish
Dey, Bidit
Gutierrez, Anabel
Dwivedi, Yogesh K.
Type of Publication: A3 Book chapter
Field of Science: 512 Business and management
Subjects:
Copyright information: © Springer Nature Switzerland AG 2020. This is a post-peer-review, pre-copyedit version of an article published in Digital and Social Media Marketing. Advances in Theory and Practice of Emerging Markets. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-24374-6_10.