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The AI Product Manager's Handbook

You're reading from  The AI Product Manager's Handbook

Product type Book
Published in Feb 2023
Publisher Packt
ISBN-13 9781804612934
Pages 250 pages
Edition 1st Edition
Languages
Author (1):
Irene Bratsis Irene Bratsis
Profile icon Irene Bratsis

Table of Contents (19) Chapters

Preface 1. Part 1 – Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
2. Chapter 1: Understanding the Infrastructure and Tools for Building AI Products 3. Chapter 2: Model Development and Maintenance for AI Products 4. Chapter 3: Machine Learning and Deep Learning Deep Dive 5. Chapter 4: Commercializing AI Products 6. Chapter 5: AI Transformation and Its Impact on Product Management 7. Part 2 – Building an AI-Native Product
8. Chapter 6: Understanding the AI-Native Product 9. Chapter 7: Productizing the ML Service 10. Chapter 8: Customization for Verticals, Customers, and Peer Groups 11. Chapter 9: Macro and Micro AI for Your Product 12. Chapter 10: Benchmarking Performance, Growth Hacking, and Cost 13. Part 3 – Integrating AI into Existing Non-AI Products
14. Chapter 11: The Rising Tide of AI 15. Chapter 12: Trends and Insights across Industry 16. Chapter 13: Evolving Products into AI Products 17. Index 18. Other Books You May Enjoy

Value metrics – evaluating performance across verticals and peer groups

No matter what domain, vertical, or peer group your AI product is in, you’re going to need to establish some way of communicating the success of your product through a combination of value (business) metrics, key performance indicators (KPIs), and objectives and key results (OKRs), along with a number of technical metrics that might be required when you’re communicating about the efficacy and success of your product to a technical audience. As with anything, if we can’t establish a baseline and see how we’ve grown from that baseline, we won’t know whether our performance is improving (and if it is, by how much) unless we track it.

In the following section, we will be looking at the various types of metrics we will start to collect on our products’ efficacy. For AI products, deciding on which metrics you will track, how you will talk about them, and what kinds...

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