Improve Customer Lifetime Value using Azure Databricks & Delta Lake

To stay competitive, businesses today need to drive new revenue growth as well as managing costs. With this in mind, understanding who the good customers are and aren't is of vital importance. Customer Lifetime Value (CLV) is an essential tool for businesses to understand their customers as it gives you insight into which customers are "worth" promoting to. Traditionally, CLV models are based on historical averages, averages derived from batch jobs, etc. In today's fast-moving world, batch jobs may not be enough; we need real-time results. This session shows how to quickly develop and deploy real-time CLV and retention analytics using Azure Databricks, ML and Delta Lake. We look at: * What Customer Lifetime Value is and how it is calculated. * The relationship between Churn and CLV * How Azure Databricks, together with Delta Lake, and ML can help you calculate CLV and make decisions based on the CLV.