A3 Book section, Chapters in research books
Using AI to Personalise Emotionally Appealing Advertisement (2020)


Mogaji, 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.), Digital and Social Media Marketing : Emerging Applications and Theoretical Development (pp. 137-150). Springer. Advances in Theory and Practice of Emerging Markets. https://doi.org/10.1007/978-3-030-24374-6_10


JYU authors or editors


Publication details

All authors or editors: Mogaji, Emmanuel; Olaleye, Sunday; Ukpabi, Dandison

Parent publication: Digital and Social Media Marketing : Emerging Applications and Theoretical Development

Parent publication editors: Rana, Nripendra P.; Slade, Emma L.; Sahu, Ganesh P.; Kizgin, Hatice; Singh, Nitish; Dey, Bidit; Gutierrez, Anabel; Dwivedi, Yogesh K.

ISBN: 978-3-030-24373-9

eISBN: 978-3-030-24374-6

Journal or series: Advances in Theory and Practice of Emerging Markets

ISSN: 2522-5006

eISSN: 2522-5014

Publication year: 2020

Pages range: 137-150

Number of pages in the book: 339

Publisher: Springer

Place of Publication: Cham

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.1007/978-3-030-24374-6_10

Publication open access: Not open

Publication channel open access:

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/67008


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.


Keywords: artificial intelligence; online advertising; precision marketing; social media

Free keywords: artificial intelligence; online behavioural advertising; personalised ad; emotional appeal; social media


Contributing organizations


Ministry reporting: Yes

Reporting Year: 2020

JUFO rating: 2


Last updated on 2021-09-08 at 13:03