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Architecting AI Solutions on Salesforce

You're reading from  Architecting AI Solutions on Salesforce

Product type Book
Published in Nov 2021
Publisher Packt
ISBN-13 9781801076012
Pages 340 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Lars Malmqvist Lars Malmqvist
Profile icon Lars Malmqvist

Table of Contents (17) Chapters

Preface 1. Section 1: Salesforce and AI
2. Chapter 1: AI Solutions on the Salesforce Einstein Platform 3. Section 2: Out-of-the-Box AI Features for Salesforce
4. Chapter 2: Salesforce AI for Sales 5. Chapter 3: Salesforce AI for Service 6. Chapter 4: Salesforce AI for Marketing and Commerce 7. Chapter 5: Salesforce AI for Industry Clouds 8. Section 3: Extending and Building AI Features
9. Chapter 6: Declarative Customization Options 10. Chapter 7: Building AI Features with Einstein Platform Services 11. Chapter 8: Integrating Third-Party AI Services 12. Section 4: Making the Right Decision
13. Chapter 9: A Salesforce AI Decision Guide 14. Chapter 10: Conclusion 15. Assessments 16. Other Books You May Enjoy

Setting up Einstein Lead Scoring and Opportunity Scoring

In the following sections, we will cover in detail Einstein Lead Scoring and Opportunity Scoring. First, we will cover the basics of Lead Scoring, then the key use cases and configuration options. We will cover the main architectural considerations for using the feature and then move on to a hands-on example. Finally, we will look at how Opportunity Scoring differs in some minor ways from Lead Scoring.

The basics of Einstein Lead Scoring

Lead Scoring is not a new invention. It refers simply to any way in which a company may numerically differentiate which leads to prioritize for distribution to sales staff, given limited sales resources. Many companies have pre-existing models, ranging from the basic (for example, the title is chief executive officer (CEO) and value > £1m) to sophisticated (for example, a statistical model informed by demographic and trend data). Einstein Lead Scoring, however, is a step up in so...

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