Subscription churn modeling | Marley Spoon case study
Putting data science to work for smarter churn prevention strategies
Marley Spoon operates on a subscription model, making retention a focal point of their growth strategy. Here’s how Faraday helped them detect churn better with data science.
Here’s the gist:
Higher churn rates make it more difficult to cover acquisition costs and scale revenue. Marley Spoon wanted a better approach to churn prediction than traditional rules-based segmentation.
Faraday built and validated a predictive churn model from a combination of Marley Spoon’s customer data and Faraday’s third-party consumer data.
Analysis and results
A comparison of Marley Spoon’s traditional approach and the Faraday churn model revealed a 5X improvement in churn prediction when using the predictive model.