Making Product Recommendations to High Value Customers with kumo AI

Learn how to predict the lifetime value of your high value customers and the products they are most likely to purchase

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overview

This solution architecture shows you how to use Kumo and Snowflake to build predictive models for delivering product recommendations to high value customers.

  • Build AI models for predicting customer lifetime value and recommending products to high value customers
  • Evaluate your predictive models with Kumo’s explainable AI tools
  • Productionize your ML workflow automatically using Kumo within your Snowflake environment

Snowflake Features Used
Quickstart
Build this solution now Product Recommendations for High LTV Customers using Kumo in Snowflake Native Apps

Solution Architecture: Making Product Recommendations to High Value Customers

  • In this use-case, you will learn how to quickly build machine learning models for personalizing communications of what you sell to your customers.
  • You will learn how to predict your highest value customers and personalize product recommendations to them for improving sales.
  • You will also learn how to productionize your predictions and shutdown your Kumo native app.

HANDS-ON TECHNICAL RESOURCES