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Using AI to personalise emotionally appealing advertisement

Using AI to personalise emotionally appealing advertisement

Mogaji, Emmanuel ORCID: 0000-0003-0544-4842, Olaleye, Sunday and Ukpadi, Dandison (2019) Using AI to personalise emotionally appealing advertisement. In: Rana, Nripendra P., Slade, Emma L., Sahu, Ganesh P., Kizgin, Hatice, Singh, Nitish, Dey, Bidit, Gutierrez, Anabel and Dwivedi, Yogesh K., (eds.) Digital and Social Media Marketing: Emerging Applications and Theoretical Development. Advances in Theory and Practice of Emerging Markets (339). Springer, Cham, Switzerland, pp. 137-150. ISBN 978-3030243746 (doi:https://doi.org/10.1007/978-3-030-24374-6_10)

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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 incorpo-rates 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 bet-ter understanding of consumers as individuals. Personalised emotionally ap-pealing advertisements will be created with this information and shared digi-tally using pragmatic advertising strategies. Theoretically, this chapter con-tributes towards the use of emerging technologies such as AI and Machine Learning for Digital Marketing, big data acquisition, management and analyt-ics and its impact on advertising effectiveness. With customer analytics mak-ing up a more significant part of big data use in sales and marketing and GDPR ensures data are legitimately collected and processed, there are practi-cal implications for Managers as well. Acknowledging that this is a concep-tual model, the critical challenges are presented. This is open for future re-search and development both from academic, digital marketing practitioners and computer scientist.

Item Type: Book Section
Uncontrolled Keywords: artificial intelligence, online behavioural advertising, personalised ad, emotional appeal, social media
Subjects: H Social Sciences > HM Sociology
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of Marketing, Events & Tourism
Last Modified: 04 Dec 2019 11:07
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/26183

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