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Machine Learning and Generative AI for Marketing

Machine Learning and Generative AI for Marketing

By : Yoon Hyup Hwang, Nicholas C. Burtch
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Machine Learning and Generative AI for Marketing

Machine Learning and Generative AI for Marketing

By: Yoon Hyup Hwang, Nicholas C. Burtch

Overview of this book

In the dynamic world of marketing, the integration of artificial intelligence (AI) and machine learning (ML) is no longer just an advantage—it's a necessity. Moreover, the rise of generative AI (GenAI) helps with the creation of highly personalized, engaging content that resonates with the target audience. This book provides a comprehensive toolkit for harnessing the power of GenAI to craft marketing strategies that not only predict customer behaviors but also captivate and convert, leading to improved cost per acquisition, boosted conversion rates, and increased net sales. Starting with the basics of Python for data analysis and progressing to sophisticated ML and GenAI models, this book is your comprehensive guide to understanding and applying AI to enhance marketing strategies. Through engaging content & hands-on examples, you'll learn how to harness the capabilities of AI to unlock deep insights into customer behaviors, craft personalized marketing messages, and drive significant business growth. Additionally, you'll explore the ethical implications of AI, ensuring that your marketing strategies are not only effective but also responsible and compliant with current standards By the conclusion of this book, you'll be equipped to design, launch, and manage marketing campaigns that are not only successful but also cutting-edge.
Table of Contents (16 chapters)
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14
Other Books You May Enjoy
15
Index

Summary

In this chapter, we went on a journey through GenAI, and ZSL, and their transformative potential in marketing content creation. We introduced foundational GenAI concepts and discussed the mechanisms that allow these models to generate text, images, and more, with a particular focus on text generation. Analyzing contextual embeddings and semantic proximity highlighted the nuances that pre-trained models like GPT and BERT bring to understanding and generating language with remarkable adaptability and accuracy.

Central to our discussion was the application of ZSL in creating marketing copy, which allows brands to generate compelling content without the need for extensive training data. We outlined a strategic process to integrate ZSL into marketing strategies with the help of examples that emphasize the importance of creating clear, contextual, and creative prompts. This step-by-step approach – defining content goals, experimenting with parameters, and refining outputs...

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Machine Learning and Generative AI for Marketing
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