We've worked with hundreds of leading retail brands that all struggle with the same issue. They invest a lot of marketing resources in acquiring new customers. But they struggle to find effective ways to get those customers to stick around and make repeat purchases. In this guide we are going to show you a better way to improve retention and reduce customer churn. It is based on the use of predictive analytics and machine learning coupled with continuous market testing to optimize retention while minimizing discounts. We’ll break it down into three phases—crawl, walk and run—that start simple and add complexity as value is delivered.
Read the guide to learn:
1. Why predictive analytics and advanced segmentation are key to reducing customer churn
2. A step-by-step approach to building a predictive churn prevention program
3. A customer-focused way to measure the success of your lifecycle marketing programs