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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aaker, D. A., & Stayman, D. M. (1992). Implementing the concept of transformational advertising. Psychology & Marketing, 9(3), 237–253.
Aguirre, E., Mahr, D., Grewal, D., de Ruyter, K., & Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34–49.
Akbarpour, S. (2018). How does GDPR impact advertising and E-commerce? Retrieved August 8, 2018, from https://www.forbes.com/sites/forbesagencycouncil/2018/05/08/how-does-gdpr-impact-advertising-and-e-commerce/#56ef557d3277.
Aksoy, Y., Oh, T., Paris, S., Pollefeys, M., Matusik, W., Aksoy, Y., Oh, T.-H., & Paris, S. (2018). Semantic soft segmentation. ACM Transactions on Graphics, 37(4), 1–13. https://doi.org/10.1145/3197517.3201275.
Alalwan, A. A., Rana, N. P., Dwivedi, Y. K., & Algharabat, R. (2017). Social media in marketing: A review and analysis of the existing literature. Telematics and Informatics, 34(7), 1177–1190.
Antón, A. I., Earp, J. B., & Young, J. D. (2010). How internet users’ privacy concerns have evolved since 2002. IEEE Security & Privacy, 8(1), 21–27.
Aswani, R., Kar, A. K., Ilavarasan, P. V., & Dwivedi, Y. K. (2018). Search engine marketing is not all gold: Insights from Twitter and SEO Clerks. International Journal of Information Management, 38(1), 107–116.
Baek, T. H., & Morimoto, M. (2012). Stay away from me. Journal of Advertising, 41(1), 59–76.
Bidalgo. (2018). Home. Retrieved February 2, 2018, from https://bidalgo.com/.
Bleier, A., & Eisenbeiss, M. (2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390–409.
Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2017). Online behavioral advertising: A literature review and research agenda. Journal of Advertising, 46(3), 363–376.
Brader, T. (2006). Campaigning for hearts and minds: How emotional appeals in political ads work. Chicago: University of Chicago Press.
Chandrashekar, A., Amat, F., Basilico, J., & Jebara, T. (2017). Artwork personalization at Netflix. Retrieved February 2, 2018, from https://medium.com/netflix-techblog/artwork-personalization-c589f074ad76.
Columbus, L. (2016). Ten ways big data is revolutionizing marketing and sales. Retrieved August 8, 2018, from https://www.forbes.com/sites/louiscolumbus/2016/05/09/ten-ways-big-data-is-revolutionizing-marketing-and-sales/#1bfc272b21cf.
Datameer. (2018). Unlocking the customer’s mind with retail analytics. Retrieved August 8, 2018, from https://www.datameer.com/blog/unlocking-customers-mind-big-data-retail-analytics/.
Dawson, P., & Lamb, M. (2016). Enhanced success with programmatic social advertising. In O. Busch (Ed.), Programmatic advertising. management for professionals (pp. 103–110). Cham: Springer.
Decrop, A. (2007). The influence of message format on the effectiveness of print advertisements for tourism destinations. International Journal of Advertising, 26(4), 505–525.
Diaz, J. (2018). This AI knows when your graphic design is good (or bad). [online] Fast Company. Available at: https://www.fastcompany.com/90171173/eyequant [Accessed 16 Jul. 2019].
Doland, A. (2016). Check out the first Ad from Mccann Japan’s ‘Ai Creative Director’. Retrieved February 2, 2018, from http://adage.com/article/creativity/check-commercial-mccann-japan-ai-creative-director/304320/.
Dwivedi, Y. K., Kapoor, K. K., & Chen, H. (2015). Social media marketing and advertising. The Marketing Review, 15(3), 289–309.
Eyequant. (2018). Home. Retrieved February 2, 2018, from http://www.eyequant.com/.
Faggella, D. (2017). Artificial intelligence and the future of programmatic advertising. Retrieved August 8, 2018, from https://www.techemergence.com/ai-future-programmatic-advertising/.
Fontjoy. (2018). https://fontjoy.com/. Retrieved February 2, 2018, from https://fontjoy.com/.
Gökerik, M., Gürbüz, A., Erkan, I., Mogaji, E., & Sap, S. (2018). Surprise me with your ads! The impacts of guerrilla marketing in social media on brand image. Asia Pacific Journal of Marketing and Logistics, 30(5), 1222–1238.
Greene, T. (2018). MIT made an image editing AI that can replace the background in any image. Retrieved February 2, 2018, from https://thenextweb.com/artificial-intelligence/2018/08/21/mit-made-an-image-editing-ai-that-can-replace-the-background-in-any-image/.
Gutierrez, A., O’Leary, S., Rana, N. P., Dwivedi, Y. K., & Calle, T. (2018). Using privacy calculus theory to explore entrepreneurial directions in mobile location-based advertising: Identifying intrusiveness as the critical risk factor. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2018.09.015.
Ha, L. (1996). Observations: Advertising clutter in consumer magazines: Dimensions and effects. Journal of Advertising Research, 36(3), 76–84.
Hitchcock, E. (2018). Five big data use cases for retail. Retrieved August 8, 2018, from https://www.datameer.com/blog/five-big-data-use-cases-retail/.
Kalyanaraman, S., & Sundar, S. S. (2006). The psychological appeal of personalized content in web portals: Does customization affect attitudes and behavior? Journal of Communication, 56(1), 110–132.
Kapoor, K. K., Tamilmani, K., Rana, N. P., Patil, P., Dwivedi, Y. K., & Nerur, S. (2018). Advances in social media research: Past, present and future. Information Systems Frontiers, 20(3), 531–558.
Kihn, M. (2016). Customer journey analytics: A manifesto. Retrieved August 8, 2018, from https://blogs.gartner.com/martin-kihn/customer-journey-analytics-a-manifesto/.
Kulbok, K. (2017). What is programmatic advertising? A beginner’s guide. Retrieved August 8, 2018, from https://www.marketingweek.com/2017/03/27/programmatic-advertising/.
Kumar, V., & Gupta, S. (2016). Conceptualizing the evolution and future of advertising. Journal of Advertising, 45(3), 302–317.
Li, Z. (2017). The “Celeb” series: A close analysis of audio-visual elements in 2008 US Presidential Campaign Ads. Undergraduate Journal of Humanistic Studies, 4(1), 1–16.
Li, C., & Liu, J. (2017). A name alone is not enough: A reexamination of web-based personalization effect. Computers in Human Behavior, 72, 132–139.
Mezo, R. E. (1997). An adaptation of aristotle: A note on the types of oratory. Rhetoric Review, 16(1), 164–165.
Mogaji, E. (2016). Emotional appeals in UK Banks’ print advertisement. Unpublished PhD thesis. Luton, Bedfordshire: University of Bedfordshire.
Mogaji, E. (2018). Emotional appeals in advertising banking services. London: Emerald.
Mogaji, E., & Danbury, A. (2017). Making the brand appealing: Advertising strategies and consumers’ attitude towards UK retail bank brands. Journal of Product & Brand Management, 26(6), 531–544.
Mogaji, E., & Erkan, I. (2019). Insight into consumer experience on UK train transportation services. Travel Behaviour and Society, 14, 21–33.
Mogaji, E., & Farinloye, T. (2017). Attitudes towards brands and advertisements: Qualitative and thematic analysis of social media data. In B. Rishi & S. Bandyopadhyay (Eds.), Contemporary issues in social media marketing (pp. 206–216). London: Routledge.
Mogaji, E., Farinloye, T., & Aririguzoh, S. (2016). Factors shaping attitudes towards UK bank brands: An exploratory analysis of social media data. Cogent Business & Management, 3(1), 1223389.
Mogaji, E., Czarnecka, B., & Danbury, A. (2018). Emotional appeals in UK business-to-business financial services advertisements. International Journal of Bank Marketing, 36(1), 208–227.
O’Guinn, T., Allen, C., & Semenik, R. (2006). Advertising and integrated brand promotion (4th ed.). Mason, OH: Thomson South-Western.
Panda, T. K., Panda, T. K., & Mishra, K. (2013). Does emotional appeal work in advertising? The rationality behind using emotional appeal to create favorable brand attitude. IUP Journal of Brand Management, 10(2), 7–23.
Persado. (2018). Home. Retrieved August 8, 2018, from https://www.persado.com/.
Phrasee. (2018). Home. Retrieved August 8, 2018, from https://phrasee.co/.
Plummer, L. (2017). Fontjoy website uses machine learning to perfectly pair fonts. Retrieved February 2, 2018, from https://www.fastcompany.com/90129005/can-a-machine-choose-fonts-and-colors-better-than-you-try-it.
Rosen, J. (2012). Who do online advertisers think you are? Retrieved February 2, 2018, from https://www.nytimes.com/2012/12/02/magazine/who-do-online-advertisers-think-you-are.html?pagewanted=all&_r=0.
Rust, R. T. (2016). Comment: Is advertising a Zombie? Journal of Advertising, 45(3), 346–347.
Salander, B. (2010). Emotionality in business-to-business marketing communications. Unpublished PhD thesis. Newcastle: University of Northumbria at Newcastle.
Schiffer, J. (2015). I second that emotion: The emotive power of music in advertising media. Retrieved December 15, 2016, from Nielsen.com: http://www.nielsen.com/us/en/insights/news/2015/i-second-that-emotion-the-emotive-power-of-music-in-advertising.html.
Shareef, M. A., Dwivedi, Y. K., Kumar, V., & Kumar, U. (2017). Content design of advertisement for consumer exposure: Mobile marketing through short messaging service. International Journal of Information Management, 37(4), 257–268.
Shareef, M. A., Mukerji, B., Alryalat, M. A., Wright, A., & Dwivedi, Y. K. (2018). Advertisements on Facebook: Identifying the persuasive elements in the development of positive attitudes in consumers. Journal of Retailing and Consumer Services, 43, 258–268.
Stanton, J. V., & Guion, D. T. (2013). Taking advantage of a vulnerable group? Emotional cues in Ads targeting parents. Journal of Consumer Affairs, 47(3), 485–517.
Takahashi, D. (2018). Bidalgo uses AI to make mobile advertising more creative. Retrieved August 8, 2018, from https://venturebeat.com/2018/07/26/bidalgo-uses-ai-to-make-mobile-advertising-more-creative/.
Tran, T. P. (2017). Personalized ads on Facebook: An effective marketing tool for online marketers. Journal of Retailing and Consumer Services, 39, 230–242.
Tucker, C. E. (2014). Social networks, personalized advertising, and privacy controls. Journal of Marketing Research, 51(5), 546–562.
Ukpabi, D., Karjaluoto, H., Olaleye, S., & Mogaji, E. (2018). Dual perspectives on the role of artificially intelligent robotic virtual agents in the tourism, travel and hospitality industries. In 11th Annual Conference of the EuroMed Academy of Business. Research Advancements in National and Global Business Theory and Practice (pp. 1355–1367). Valletta, Malta: EuroMed Academy of Business.
Ukpabi, D., Karjaluoto, H., Olaleye, S., & Mogaji, E. (2019). Influence of offline activities and customer value creation on online travel community continuance usage intention. In Information and communication technologies in tourism (pp. 450–460). Cham: Springer.
Vicioso, S. (2015). Programmatic advertising 101: How it works. Retrieved February 2, 2018, from http://www.seerinteractive.com/blog/programmatic-advertising-101-works/.
Williams, E. (2018). The role of AI in redefining the programmatic advertising experience. Retrieved August 8, 2018, from https://www.martechadvisor.com/articles/ads/the-role-of-ai-in-redefining-the-programmatic-advertising-experience/.
Wilson, M. (2017). Can a machine choose fonts and colors better than you? Try it. Retrieved February 2, 2018, from https://www.fastcompany.com/90129005/can-a-machine-choose-fonts-and-colors-better-than-you-try-it.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Mogaji, E., Olaleye, S., Ukpabi, D. (2020). Using AI to Personalise Emotionally Appealing Advertisement. In: Rana, N.P., et al. 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
Download citation
DOI: https://doi.org/10.1007/978-3-030-24374-6_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-24373-9
Online ISBN: 978-3-030-24374-6
eBook Packages: Business and ManagementBusiness and Management (R0)