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AI-Powered Commerce

You're reading from   AI-Powered Commerce Building the products and services of the future with Commerce.AI

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781803248981
Length 256 pages
Edition 1st Edition
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Authors (2):
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Andy Pandharikar Andy Pandharikar
Author Profile Icon Andy Pandharikar
Andy Pandharikar
Frederik Bussler Frederik Bussler
Author Profile Icon Frederik Bussler
Frederik Bussler
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1:Benefits of AI-Powered Commerce
2. Chapter 1: Improving Market Opportunity Identification FREE CHAPTER 3. Chapter 2: Creating Product Ideas 4. Chapter 3: Understanding How to Predict Industry-Wide Trends Using Big Data 5. Section 2:How Top Brands Use Artificial Intelligence
6. Chapter 4: Applying AI for Innovation – Luxury Goods Deep Dive 7. Chapter 5: Applying AI for Innovation – Wireless Networking Deep Dive 8. Chapter 6: Applying AI for Innovation –Consumer Electronics Deep Dive 9. Chapter 7: Applying AI for Innovation – Restaurants Deep Dive 10. Chapter 8: Applying AI for Innovation – Consumer Goods Deep Dive 11. Section 3:How to Use Commerce.AI for Product Ideation, Trend Analysis, and Predictions
12. Chapter 9: Delivering Insights with Product AI 13. Chapter 10: Delivering Insights with Service AI 14. Chapter 11: Delivering Insights with Market AI 15. Chapter 12: Delivering Insights with Voice Surveys 16. Other Books You May Enjoy

Chapter 2: Creating Product Ideas

Coming up with great product ideas isn't easy. It's both an art and a science, and those with the ability to come up with great ideas are remembered in history, from people such as Steve Jobs to Mark Zuckerberg.

In this chapter, we'll explore the five pillars of AI, which are driving new and innovative ways to create product ideas: language understanding, visual understanding, information extraction, information organization, and creative AI. Understanding the pillars of AI will help you become more strategic about how you plan, manage, and invest in your AI projects.

For instance, some product teams might like to use AI to generate new product designs, which would focus on the pillar of visual understanding, while others might like to use AI to understand desired customer features that will lay the framework for new products, which would involve pillars such as language understanding and information extraction.

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