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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
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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

Analyzing product data for restaurants

The restaurant industry is a highly fragmented market with an enormous variety of products and services available to consumers. As a result, it can be difficult for restaurateurs to understand the data they need to drive meaningful innovation in their businesses.

This section introduces several different ways that data can be used as a tool for innovation within the restaurant industry, including predicting food item success, predicting competitor performance, new profile discovery, and more.

Predicting how food items are likely to perform

One big way to use data for restaurant innovation is to predict how food items will perform in-market. By analyzing the performance of food items in the restaurant industry at large, restaurateurs can identify which food items are likely to be most popular with consumers. This information can then be used to inform business decisions about menu items, pricing, and marketing campaigns.

Traditionally...

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