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Inteligência artificial e design generativo como alicerce na materialização de cenários de mercado para o planeamento publicitário

Authors: Martins, Carolina França Teles de Almeida;

Inteligência artificial e design generativo como alicerce na materialização de cenários de mercado para o planeamento publicitário

Abstract

O design generativo utiliza algoritmos e processos computacionais para criar soluções baseadas em parâmetros previamente estabelecidos, já a inteligência artificial, que se encontra em constante evolução, destaca-se por ter a capacidade de analisar grandes volumes de dados e identificar padrões que não são facilmente visíveis à perceção humana. Vários autores já estudaram sobre estas áreas, mas nunca sobre a sua união. Este estudo tem como objetivo demonstrar como a união entre o design generativo e a inteligência artificial pode revolucionar a abordagem tradicional no planeamento publicitário, uma vez que, ao trabalharem juntos podem fornecer dados e insights de forma rápida e em grande escala, promovendo uma maior eficiência. Este estudo pretende ainda inovar a forma como se criam campanhas e abrir portas para um mundo de estratégias mais criativas e funcionais. Para esse efeito, a metodologia que se pretende utilizar passa pela análise de cenários de mercado materializados através de design generativo e inteligência artificial, em forma de entrevistas com profissionais da área do marketing e da publicidade, para assim verificar se a combinação destas duas ferramentas pode então fornecer cenários realistas, com o objetivo de aprimorar ainda mais o trabalho dos planeadores estratégicos. No final, espera-se comprovar a hipótese de pesquisa e validar se realmente o design generativo e a inteligência artificial podem ser uma mais-valia na vertente do planeamento publicitário, tornando o mercado da publicidade mais dinâmico e competitivo.

Generative design uses algorithms and computational processes to create solutions based on previously established parameters, while artificial intelligence, which is constantly evolving, stands out for its ability to analyze large volumes of data and identify patterns that are not easily visible to human perception. Several authors have studied these areas, but never their union. This study aims to demonstrate how the union between generative design and artificial intelligence can revolutionize the traditional approach to advertising planning, since by working together they can provide data and insights quickly and on a large scale, promoting greater efficiency. This study also aims to innovate the way campaigns are created and open the door to a world of more creative and functional strategies. To this end, the methodology to be used involves analyzing market scenarios materialized through generative design and artificial intelligence, in the form of interviews with marketing and advertising professionals, to see if the combination of these two tools can then provide realistic scenarios, with the aim of further improving the work of strategic planners. In the end, we hope to prove the research hypothesis and validate whether generative design and artificial intelligence can really be an asset in advertising planning, making the advertising market more dynamic and competitive.

Country
Portugal
Keywords

Publicidade, Design, Cenários de mercado, Inteligência artificial, Planeamento publicitário

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green