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Get Smart with Salesforce Einstein

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  1. Salesforce Einstein Basics

    Get Started with Einstein
  2. Get Started with Einstein
    7 Topics
  3. Learn About Einstein Out-Of-The-Box Applications
    7 Topics
  4. Responsible Creation of Artificial Intelligence
    Use the Einstein Platform
    9 Topics
  5. Understand the Ethical Use of Technology
    8 Topics
  6. Learn the Basics of Artificial Intelligence
    5 Topics
  7. Recognize Bias in Artificial Intelligence
    6 Topics
  8. Einstein Bots Basics
    Remove Bias from Your Data and Algorithms
    6 Topics
  9. Learn About Einstein Bots
    6 Topics
  10. Plan Your Bot Content
    4 Topics
  11. Einstein Next Best Action
    Learn the Prerequisites and Enable Einstein Bots
    3 Topics
  12. Get Started with Einstein Next Best Action
    9 Topics
  13. Sales Cloud Einstein
    Understand How Einstein Next Best Action Works
    7 Topics
  14. Increase Sales Productivity
    5 Topics
  15. Automate Sales Activities
    5 Topics
  16. Target the Best Leads
    3 Topics
  17. Close More Deals
    6 Topics
  18. Connect with Your Customers and Create New Business
    4 Topics
  19. Sales Cloud Einstein Rollout Strategies
    Improve Sales Predictions
    4 Topics
  20. Use AI to Improve Sales
  21. Start with a Plan
  22. Set Goals and Priorities
  23. Get Ready for Einstein
  24. Quick Start: Einstein Prediction Builder
    Start Using Sales Cloud Einstein
  25. Sign Up for an Einstein Prediction Builder Trailhead Playground
  26. Create a Formula Field to Predict
  27. Enrich Your Prediction
  28. Build a Prediction
  29. Quick Start: Einstein Image Classification
    Create a List View for Your Predictions
  30. Get an Einstein Platform Services Account
  31. Get the Code
  32. Create a Remote Site
  33. Create the Apex Classes
  34. Einstein Intent API Basics
    Create the Visualforce Page
  35. Get Started with Einstein Language
  36. Set Up Your Environment
  37. Create the Dataset
  38. Train the Dataset and Create a Model
  39. Put Predictions into Action with Next Best Action
    Use the Model to Make a Prediction
  40. Learn the Basics and Set Up a Custom Playground
  41. Define and Build a Prediction
  42. Customize Your Contact and List Displays
  43. Create Recommendations for Einstein Next Best Action
  44. Create a Next Best Action Strategy
  45. Add Next Best Action to Your Contacts

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Several years ago, Cantaloupe, the competitor that Ava mentioned to you, dreamed of using AI to transform its enterprise sales team. So Cantaloupe hired an expert in AI management, who helped acquire a burgeoning AI start-up. The deal included a crack team filled with the best minds in data mining, data science, and computer architecture. The team spent the next 5 years:

  • Harnessing big data
  • Cataloging the sales information needed to win deals
  • Developing complex data science formulas
  • Building sophisticated apps to surface insights and recommendations

The results were astounding: Cantaloupe transformed its business and went on to lead the industry. And it only cost the company a few million dollars to develop their AI formula.

Cantaloupe transformed

It’s not just companies like Cantaloupe. In recent years, AI solutions have fetched a hefty price. According to the Wall Street Journal, AI platforms for business started off as a multimillion-dollar enterprise. The Epoch Times noted some of the more well-known AI solution acquisitions.

  • Google paid $600 million for an AI solution called DeepMind, which beat a human world champion at the board game Go
  • Twitter paid $150 million for Magic Pony, an image-processing platform
  • Microsoft paid $200 million for Equivio, a machine learning start-up
  • Splunk paid $190 million for Caspida, a cybersecurity AI firm
  • Apple paid $30 million for MapSense, an AI mapping company

Most AI solutions for sales require numerous people working on big data, sales info, algorithms, and apps. All of that is expensive.

Table 1. AI for Sales Inventory List
Item Personnel Description
Big Data
  • Data entry staff
  • Database administrator
  • IT technicians
  • Input all data into one system.
  • Develop ways of cleaning and normalizing the data.
  • Acquire and maintain computers that store and process all the data.
Sales Info
  • Executive management
  • Sales managers
 Outline what reps do at each stage of the sales process and determine which insights can be helpful. Insights differ during each stage: prospecting for leads, closing deals, and maintaining customer relationships.
Algorithms Data scientists Develop sophisticated computer programs that learn from new data.
Apps Engineers Create and maintain apps to display the results of the algorithms.
Total Cost $30–600 million

The high price that companies like Cantaloupe have spent on AI solutions is exactly what Ava worries about. With a tight budget, Honeydew is certainly no Cantaloupe.

You start to feel a bit discouraged. Honeydew can’t afford a team of scientists working years to come up with an AI solution.

Most sales ops managers would be ready to give up at this point. But you’re not most sales ops managers, are you?