Discover Academic Papers about AI and Digital Marketing
This section provides a review of academic papers that explore the intersection of artificial intelligence and marketing.
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It highlights key findings, methodologies, and insights from various studies, offering a deeper understanding of how AI is transforming marketing strategies and consumer engagement.
Staying informed on the latest trends and developments in the field.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova
The paper marks a leap in natural language processing (NLP). BERT introduced a new way of language understanding by utilizing bidirectional transformers, which allow models to look at text from both left-to-right and right-to-left simultaneously.
This stands in contrast to prior models, such as OpenAI’s GPT, which only processed text in a left-to-right manner.
Language Models are Few-Shot Learners
Tom B. Brown Benjamin Mann Nick Ryder, Melanie Subbiah
The paper "Language Models are Few-Shot Learners" by OpenAI researchers (including Tom B. Brown) introduced GPT-3, a language model that marked a major step forward in how AI can understand and generate human-like text.
This paper is important for understanding OpenAI's current models and AI as a whole.
Generative AI and Usage in Marketing Classroom
Min Ding1 · Songting Dong2 · Rajdeep Grewal3
The paper offers insights into how Generative AI (GenAI) is reshaping marketing practices and education. AI-powered content creation, chatbots, and personalization are becoming the new norms, bringing efficiency and creativity together like never before.
A strategic framework for artificial intelligence in marketing
Ming-Hui Huang & Roland T. Rust
A roadmap for how businesses can harness AI to elevate their marketing strategies. The framework breaks down AI into three key types:
1. Mechanical AI is all about automating repetitive tasks like data collection, pricing, and logistics.
2. Thinking AI focuses on personalization. It analyzes customer data to deliver tailored experiences.
3. Feeling AI is designed to build emotional connections. It uses tools like sentiment analysis and chatbots that can simulate empathetic responses.
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine
By Harsha Nori , Yin Tat Lee , Sheng Zhang*, et al.
Can an AI model outsmart doctors? It just did. GPT-4, a generalist AI model, beat out specialized medical AI at tasks only experts thought it could handle. The same strategies that helped GPT-4 outperform in medicine could be the key to revolutionizing your marketing strategy.
Transforming Digital Marketing with Gen AI"
by Tasin Islam, et. al.
A virtual try-on model powered by Generative AI can dramatically enhance the online shopping experience by reducing guesswork for customers. By improving accuracy and personalization, this feature can help fashion retailers increase conversions, reduce returns, and boost overall customer satisfaction. Monitoring the right metrics—like conversion rate, return rate, and customer satisfaction—ensures that the feature continuously adds value to the business.
Artificial Intelligence in Digital Marketing: Insights from a
Comprehensive Review
Christos Ziakis and Maro Vlachopoulou
Discover how AI is revolutionizing digital marketing with key themes like social media strategies, personalized advertising, and e-commerce growth. Learn what businesses and investors need to know to stay ahead of AI-driven trends in marketing.
This paper highlights the transformative role AI plays in digital marketing and provides a roadmap for businesses to strategically integrate AI into their marketing efforts. For those in the industry, understanding these themes is essential to navigate the future landscape effectively.