Eficácia e impacto na experiência do cliente: um estudo sobre os modelos generativos ChatGPT e Gemini
Authors/Creators
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1.
Fatec Praia Grande
Description
Este estudo analisa a aplicação dos modelos generativos ChatGPT (OpenAI) e Gemini (Google DeepMind) na fidelização e engajamento de clientes. Por meio de análise comparativa, identificamos que o Gemini se destaca em tarefas multimodais, como reconhecimento visual, enquanto o ChatGPT é mais eficaz em interações textuais e personalização. A escolha do modelo deve considerar o contexto de aplicação e o perfil do usuário. Discutimos limitações técnicas e o potencial dessas tecnologias na construção de relações mais eficazes entre empresas e consumidores. Concluímos que ambos os modelos oferecem benefícios significativos (aumento de até 50% no engajamento e redução de 45% no tempo de resposta), mas sua eficácia depende de implementação estratégica.
Versão publicada na Revista Processando o Saber:
https://www.fatecpg.edu.br/revista/index.php/ps/article/view/396
Abstract (English)
This study examines the application of generative AI models, ChatGPT (OpenAI) and Gemini (Google DeepMind), in customer engagement and retention. Through comparative analysis, we find that Gemini excels in multimodal tasks, such as visual recognition, while ChatGPT is more effective in textual interactions and personalization. Model selection should consider the application context and user profile. We discuss technical limitations and the potential of these technologies in building more effective relationships between companies and consumers. We conclude that both models offer significant benefits (up to 50% increase in engagement and 45% reduction in response time), but their effectiveness depends on strategic implementation.
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Additional details
Additional titles
- Translated title (English)
- Effectiveness and impact on customer experience: a study on the generative models Chatgpt and Gemini
Related works
- Is published in
- Journal article: https://www.fatecpg.edu.br/revista/index.php/ps/article/view/396 (URL)
Dates
- Issued
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2025-06-06
References
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