Guide

Applying machine learning to loyalty

Applying machine learning to loyalty

Htk guide

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Customers won’t wait for your systems to catch-up

Today’s businesses leverage data for a variety of purposes. For loyalty programs, the most common
use cases are recency, frequency and monetary value (RFM) or customer lifetime value (CLV) mod- els; churn/lapse risk models; cross-sell/redemption analytics; and behavioral clustering.


Nevertheless, for most businesses, their insight is a static view, updated periodically. Although useful for planning, the insight is out of date the next day, or even in the next few minutes. Without ML, the customer is on to the next thing.

Get tips and advice for a applying Machine Learning to your loyalty program

In this ebook, you’ll find actionable tips for considering Machine Learning models and how you can empower your loyalty programs with powerful automation and testing.

Download it now to find out:

  • engineer a successful ML deployment
  • how to automate as you go, and
  • why periodic death can be an opportunity.