Smart Advertising: AI Driven Innovation and Technological Disruption in the Advertising Ecosystem

Authors

DOI:

https://doi.org/10.4185/10.4185/RLCS-2022-1693

Keywords:

artificial intelligence, advertising, programmatic, creativity, automation, deep fake, big data

Abstract

Introduction: The impact of artificial intelligence (AI) in media industries has received increasing attention in recent years. Research literature in this regard has focused on content production and distribution sectors, leaving advertising in a discreet background. This article aims to take the study of AI and advertising to the forefront, identifying the scope of current research on the subject and offering a map of the research trends, drawing them as a key vector of technology-based innovation in the media ecosystem. Methodology: In order to do so, a qualitative scoping review of the current research literature on AI and advertising has been developed, completed by the contribution of professional reports from the sector. Results and discussion: The existing literature points to the efficiency in large unstructured data sets processing, predictive / prescriptive analysis, natural language recognition and image recognition, as automation as the main AI innovation vectors. The disruptive impact of AI affects all phases of the advertising process: market research and analysis, creativity, media planning and buying, and effectiveness evaluation. Conclusions: Research tends to perpetuate the traditional structure of the advertising process and obviates the ecosystem dimension of innovation, which transforms actors and their relationships.

Downloads

Download data is not yet available.

Author Biographies

Inmaculada José . Martínez Martínez, University of Murcia

Ph.D. in Information Sciences (Advertising) from the Universidad Complutense de Madrid and MA in Marketing from the Know How Business School. She is a full professor of Advertising Business at the Faculty of Communication and Documentation of the Universidad de Murcia. She recently published ‘El impacto de la tecnología digital en el sector publicitario’ (2019). She is co-director of the Mobile Media Research Lab since 2014 and has been chief researcher of the R&D project "MOB AD: Impacto de la tecnología móvil en la comunicación estratégica y publicitaria" (19451/PI/14) and is currently participating in the R&D project INNOVACOM: Ecosistemas de innovación en las industrias de la comunicación: Actores, tecnologías y configuraciones para la generación de innovación en contenido y comunicación (PID2020-114007RB-I00).

 

inmartin@um.es  

Índice H: 19

Orcid ID: http://orcid.org/0000-0003-3807-1325

Google Scholar: https://scholar.google.es/citations?user=hTWUPqcAAAAJ&hl=es

ResearchGate: https://www.researchgate.net/profile/Inmaculada-Martinez-2

Scopus ID: 35912729600

Juan Miguel Aguado, Universidad de Murcia

Ph.D. in Information Sciences and Postgraduate in Social Research from the Polish Academy of Sciences (Warsaw). Professor of Communication Theory at the Faculty of Communication and Documentation of the Universidad de Murcia, his recent publications include: ‘El impacto de la tecnología digital en el sector publicitario’ (2019) and ‘Mediaciones Ubicuas: Ecosistema móvil, gestión de identidad y nuevo espacio público’ (2020). He is co-director and founder of the Mobile Media Research Lab since 2014. He is currently CR of the R&D project INNOVACOM: Ecosistemas de innovación en las industrias de la comunicación: Actores, tecnologías y configuraciones para la generación de innovación en contenido y comunicación (PID2020- 114007RB-I00).

jmaguado@um.es
Índice H: 23
Orcid ID: http://orcid.org/0000-0002-8922-3299

Google Scholar: https://scholar.google.es/citations?hl=es&user=X9vZoBEAAAAJ

ResearchGate: https://www.researchgate.net/profile/Juan-Aguado-9

Scopus ID: 13410977200

Paloma del Henar Sánchez Cobarro, Universidad de Murcia

She is a professor at the Faculty of Communication and Documentation at the Universidad de Murcia. She holds a Ph.D. in Communication Sciences. She has a degree in Advertising and Public Relations and a degree in Journalism. She is a communication consultant in public and private organizations. She has published articles in scientific journals in the field of communication and specialized book chapters on corporate communication and organizational strategy. She has participated in several competitive R+D+I projects both at the national and regional levels. She is currently part of the team of the R&D project INNOVACOM: Ecosistemas de innovación en las industrias de la comunicación: Actores, tecnologías y configuraciones para la generación de innovación en contenido y comunicación (PID2020-114007RB-I00). Her main lines of research are research trends in communication, development of professional skills, and strategic communication. 

palomahenar.sanchez@um.es

Índice H: 7

Orcid ID: https://orcid.org/ 0000-0002-4018-6271    

Google Scholar: https://scholar.google.es/citations?user=HHFUBPkAAAAJ&hl=es

ResearchGate: https://www.researchgate.net/profile/Paloma-Sanchez-Cobarro

 

References

Acquisti, A., Taylor, C., y Wagman, L. (2016). «The economics of privacy». Journal of Economic Literature, 54(2), 442-92. https://doi.org/10.1257/jel.54.2.442

Adform (2019) Fact or fiction? The threat of cookie Apocalypse. IAB Europe whitepaper. https://iabeurope.eu/wp-content/uploads/2019/11/Fact-or-Fiction-The-threat-of-a-Cookie-Apocalypse.pdf

Albinali, E. A. y Hamdan, A. (2020, November). The implementation of artificial intelligence in social media marketing and its impact on consumer behavior: evidence from Bahrain. International Conference on Business and Technology (pp. 767-774). Springer, Cham. https://doi.org/10.1007/978-3-030-69221-6_58

Ahn, J. B. (2020). A Study on Advertising Future Development Roadmap in the Fourth Industrial Revolution Era. International Journal of Internet, Broadcasting and Communication, 12(2), 66-76. https://doi.org/10.7236/IJIBC.2020.12.2.66

Ali, W. y Hassoun, M. (2019). Artificial intelligence and automated journalism: Contemporary challenges and new opportunities. International journal of media, journalism and mass communications, 5(1), 40-49. http://dx.doi.org/10.20431/2454-9479.0501004

Arvidsson, A. y Colleoni, E. (2012). Value in Informational Capitalism and on the Internet. The Information Society, 28(3), 135-150. https://doi.org/10.1080/01972243.2012.669449

Allam, S. (2016). The Impact of Artificial Intelligence on Innovation-An Exploratory Analysis. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320-2882. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3821173

Barker, A. (2020) “’Cookie Apocalypse’ forces profound changes in online advertising”, Financial Times, 02/26/2020 https://www.ft.com/content/169079b2-3ba1-11ea-b84f-a62c46f39bc2

Bradley, S. (2021). “Could AI product placement help brands break through the ad break?” The Drum, 05/05/2021. https://www.thedrum.com/news/2021/05/05/could-ai-product-placement-help-brands-break-through-the-ad-break

Buckley, D. (2021). Privacy enhancing technologies for trustworthy use of data. Centre for Data Ethics and Innovation, Reino Unido. https://cdei.blog.gov.uk/2021/02/09/privacy-enhancing-technologies-for-trustworthy-use-of-data/

Busch, O. (2019) Programmatic Advertising. The Successful Transformation to Automated, Data-Driven Marketing in Real-Time. Berlin, Springer.

Campbell, C., Plangger, K., Sands, S. y Kietzmann, J. (2021). Preparing for an era of deepfakes and AI-generated ads: A framework for understanding responses to manipulated advertising. Journal of Advertising, 1-17. https://doi.org/10.1080/00913367.2021.1909515

Carrillo-Durán, M. V. y Rodríguez-Silgado, A. (2018). El ecosistema programático. La nueva publicidad digital que conecta datos con personas. El profesional de la información, 27(1), 195-201. https://doi.org/10.3145/epi.2018.ene.18

Chen, G., Xie, P., Dong, J. y Wang, T. (2019). Understanding programmatic creative: The role of AI. Journal of Advertising, 48(4), 347-355. https://doi.org/10.1080/00913367.2019.1654421

Christiansen, L. (2011). Personal privacy and internet marketing: an impossible conflict or a marriage made in heaven?. Business horizons, v. 54, n. 6, pp. 509-514.

Cillo, V., Petruzzelli, A. M., Ardito, L. y Del Giudice, M. (2019). Understanding sustainable innovation: A systematic literature review. Corporate Social Responsibility and Environmental Management, 26(5), 1012-1025. https://doi.org/10.1002/csr.1783

Codina, Lluís (2020). Revisiones sistematizadas en Ciencias Humanas y Sociales. 3: Análisis y Síntesis de la información cualitativa. En: Lopezosa C., Díaz-Noci J., Codina L. (Eds.) Methodos Anuario de Métodos de Investigación en Comunicación Social, 1. Barcelona: Universitat Pompeu Fabra; 2020. p. 73-87. https://doi.org/10.31009/methodos.2020.i01.07

Duan, C., & Yang, H. (2018). Data, Algorithmic Model, and Decision-Making: The Development of Computational Advertising. Journalism Bimonthly, 2018(1), 128-136. https://en.cnki.com.cn/Article_en/CJFDTotal-XWDX201801017.htm

Enache, M. C. (2020). AI for Advertising. Annals of the University Dunarea de Jos of Galati: Fascicle: I, Economics & Applied Informatics, 26(1). https://doi.org/10.35219/eai1584040978

EU (2021). The Digital Services Act Package. https://digital-strategy.ec.europa.eu/en/policies/digital-services-act-package

Grant, Maria J. y Booth, Andrew (2009). A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information and Libraries Journal, 26, pp.91–108. https://doi.org/10.1111/j.1471-1842.2009.00848.x

Hancock, J. T., Naaman, M. y Levy, K. (2020). AI-mediated communication: definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication, 25(1), 89-100. https://doi.org/10.1093/jcmc/zmz022

Helberger, N., Huh, J., Milne, G., Strycharz, J. y Sundaram, H. (2020). Macro and exogenous factors in computational advertising: Key issues and new research directions. Journal of Advertising, 49(4), 377-393. https://doi.org/10.1080/00913367.2020.1811179

Hill, R. K. (2016). What an algorithm is. Philosophy & Technology, 29(1), 35-59. https://doi.org/10.1007/s13347-014-0184-5

Huang, M. H. y Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), 30-50. https://doi.org/10.1007/s11747-020-00749-9

Houle, O. y Mauss, J.C. (2021) The Impact of Cookie Apocalypse on Digital Media. Ads. https://www.adviso.ca/en/blog/guides-en/attribute-measure-retarget/

ICO (2019). Update Report into Adtech and Real Time Bidding. June, 20, 2019. https://ico.org.uk/media/about-the-ico/documents/2615156/adtech-real-time-bidding-report-201906-dl191220.pdf

Kietzmann, J., Paschen, J. y Treen, E. (2018). Artificial intelligence in advertising: How marketers can leverage artificial intelligence along the consumer journey. Journal of Advertising Research, 58(3), 263-267. https://doi.org/10.2501/JAR-2018-035

Koren, Y., Somekh, O., Shahar, A., Itzhaki, A., Cohen, T., Krasteva, M. y Shadi, T. (2020). Dynamic Creative Optimization in Verizon Media Native Advertising. En: 2020 IEEE International Conference on Big Data (Big Data) (pp. 1654-1662). IEEE. https://doi.org/10.1109/BigData50022.2020.9378251

Kumar, V., & Shaphali G. (2016). Conceptualizing the Evolution and Future of Advertising, Journal of Advertising, 45 (3), 302–17. https://doi.org/10.1080/00913367.2016.1199335

Kumar, V., Rajan, B., Venkatesan, R., y Lecinski, J. (2019). Understanding the role of artificial intelligence in personalized engagement marketing. California Management Review, 61(4), 135-155. https://doi.org/10.1177/0008125619859317

Lee, H. y Cho, C. H. (2020). Digital advertising: present and future prospects. International Journal of Advertising, 39(3), 332-341. https://doi.org/10.1080/02650487.2019.1642015

Lee, J., Suh, T., Roy, D. y Baucus, M. (2019). Emerging technology and business model innovation: the case of artificial intelligence. Journal of Open Innovation: Technology, Market, and Complexity, 5(3), 44. https://doi.org/10.3390/joitmc5030044

Li, H. (2019). Special section introduction: Artificial intelligence and advertising. Journal of advertising, 48(4), 333-337. https://doi.org/10.1080/00913367.2019.1654947

Liu, X. (2019), A big data approach to examining social bots on Twitter. Journal of Services Marketing, 33 (4), 369-379. https://doi.org/10.1108/JSM-02-2018-0049

Malthouse, E. C. y Li, H. (2017) Opportunities for and Pitfalls of Using Big Data in Advertising Research, Journal of Advertising, 46:2, 227-235, https://doi.org/10.1080/00913367.2017.1299653

Malthouse, E. C., Maslowska, E., y Franks, J. U. (2018). Understanding programmatic TV advertising. International Journal of Advertising, 37(5), 769-784. https://doi.org/10.1080/02650487.2018.1461733

Manfredi, J. L. y Ufarte, M. J. (2020). Inteligencia artificial y periodismo: una herramienta contra la desinformación. Revista CIDOB d'Afers Internacionals, 49-72. https://doi.org/10.24241/rcai.2020.124.1.49

Martínez, I. J., Aguado, J. M. y Boeykens, Y. (2017). Implicaciones éticas de la automatización de la publicidad digital: caso de la publicidad programática en España. Profesional de la Información, 26(2), 201-210. http://www.elprofesionaldelainformacion.com/contenidos/2017/mar/06.pdf

Martínez, I.J. y Aguado, J.M. (2019). El impacto de la tecnología digital en el sector publicitario. Universidad de Murcia. https://doi.org/10.5281/zenodo.3737948

Mittelstadt, B. D.; Allo, P.; Taddeo, M.; Wachter, S. y Floridi, L. (2016). «The ethics of algorithms: Mapping the debate». Big Data & Society, 3(2), 2053951716679679. https://doi.org/10.1177/2053951716679679

Napoli, P. M. (2014). Automated media: An institutional theory perspective on algorithmic media production and consumption. Communication Theory, 24(3), 340–360. https://doi.org/10.1111/comt.2014.24.issue-3

Qin, X. y Jiang, Z. (2019). The impact of AI on the advertising process: The Chinese experience. Journal of Advertising, 48(4), 338-346. https://doi.org/10.1080/00913367.2019.1652122

Palomo-Domínguez, I. (2021). Del mito a la viralidad. El caso de la campaña de Cruzcampo que resucitó a Lola Flores. aDResearch ESIC 26, e262. https://doi.org/10.7263/adresic-026-02

Pärssinen, M.; Kotila, M.; Cuevas, R.; Phansalkar, A. y Manner, J. (2018). Is Blockchain Ready to Revolutionize Online Advertising?. IEEE Access. pp. 1-1. https://doi.org/10.1109/ACCESS.2018.2872694

Paschen, U., Pitt, C. y Kietzmann, J. (2020). Artificial intelligence: Building blocks and an innovation typology. Business Horizons, 63(2), 147-155. https://doi.org/10.1016/j.bushor.2019.10.004

Rodgers, S (2021) Themed Issue Introduction: Promises and Perils of Artificial Intelligence and Advertising, Journal of Advertising, 50:1, 1-10, https://doi.org/10.1080/00913367.2020.1868233

Rodrigo-Martín, L., Rodrigo-Martín, I. y Muñoz-Sastre, D. (2021). Los Influencers Virtuales como herramienta publicitaria en la promoción de marcas y productos. Estudio de la actividad comercial de Lil Miquela. Revista Latina de Comunicación Social, (79), 69-90. https://doi.org/10.4185/RLCS-2021-1521

Shumanov, M., Cooper, H. y Ewing, M. (2021), "Using AI predicted personality to enhance advertising effectiveness", European Journal of Marketing, pre-print. https://doi.org/10.1108/EJM-12-2019-0941

Skiera, B. (2016), Data, Data, and Even More Data: Harvesting Insights from the Data Jungle, GfK Marketing Intelligence Review, 8 (2), 10–17. https://doi.org/10.1515/gfkmir-2016-0010

Song, M. (2019). A Study on Artificial Intelligence Based Business Models of Media Firms. International Journal of Advanced Smart Convergence, 8(2), 56-67. https://doi.org/10.7236/IJASC.2019.8.2.56

Thomas, V. L. y Fowler, K. (2021). Close encounters of the AI kind: Use of AI influencers as Brand endorsers. Journal of Advertising, 50(1), 11-25. https://doi.org/10.1080/00913367.2020.1810595

Túñez-López, J. M., Toural-Bran, C. y Cacheiro-Requeijo, S. (2018). Uso de bots y algoritmos para automatizar la redacción de noticias: percepción y actitudes de los periodistas en España. El Profesional de la Información, 27(4), 750-758. https://doi.org/10.3145/epi.2018.jul.04

Vakratsas, D. y Wang, X. (2020). Artificial intelligence in advertising creativity. Journal of Advertising, 50(1), 39-51. https://doi.org/10.1080/00913367.2020.1843090

Watts, J. y Adriano, A. (2021). Uncovering the sources of machine-learning mistakes in advertising: Contextual bias in the evaluation of semantic relatedness. Journal of Advertising, 50(1), 26-38. https://doi.org/10.1080/00913367.2020.1821411

Yang, Y., Yang, Y. C., Jansen, B. J. y Lalmas, M. (2017). Computational advertising: A paradigm shift for advertising and marketing?. IEEE Intelligent Systems, 32(3), 3-6. https://doi.org/10.1109/MIS.2017.58

Published

2022-05-11

How to Cite

Martínez Martínez, I. J. ., Aguado, J. M., & Sánchez Cobarro, P. del H. . (2022). Smart Advertising: AI Driven Innovation and Technological Disruption in the Advertising Ecosystem. Revista Latina De Comunicación Social, (80), 69–90. https://doi.org/10.4185/10.4185/RLCS-2022-1693

Issue

Section

Application of artificial intelligence in communication